microfluidic microarray for pathogenic dna...
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MICROFLUIDIC MICROARRAY FOR PATHOGENIC DNA
ANALYSIS: SINGLE-BASE-PAIR-MISMATCH DISCRIMINATION, AND MODELING/SIMULATION OF
CENTRIFUGAL FLOWS AND DYNAMIC HYBRIDIZATION
by
Lin Wang M.Sc., Northwest University, 2002
B.Sc., Ocean University of Qingdao, 1994
THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
In the Department of Chemistry
Faculty of Science
© Lin Wang 2012 SIMON FRASER UNIVERSITY
Spring 2012
All rights reserved. However, in accordance with the Copyright Act of Canada, this work may be reproduced, without authorization, under the conditions for Fair Dealing. Therefore, limited reproduction of this work for the purposes of private
study, research, criticism, review and news reporting is likely to be in accordance with the law, particularly if cited appropriately.
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APPROVAL
Name: Lin Wang Degree: Doctor of Philosophy Title of Thesis: Microfluidic Microarray for Pathogenic DNA
Analysis: Single-Base-Pair-Mismatch Discrimination, and Modeling/Simulation of Centrifugal Flows and Dynamic Hybridization
Examining Committee: Chair: Dr. Michael H. Eikerling
Associate Professor, Chemistry
______________________________________
Dr. Paul C.H. Li, Senior Supervisor Professor, Chemistry
______________________________________
Dr. George R. Agnes, Supervisor Professor, Chemistry
______________________________________
Dr. Peter D. Wilson, Supervisor Associate Professor, Chemistry
______________________________________
Dr. Bonnie Gray, Internal Examiner Associate Professor, Engineering Science
______________________________________
Dr. Edward P.C. Lai Professor, Chemistry Carleton University
Date Defended/Approved: January 16, 2012
Partial Copyright Licence
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ABSTRACT
In the development of surface-based biosensors, the combination of
microfluidic technology with the DNA microarray chip has been realized with the
intersection method. The method shows the advantages of less sample usage,
multiple sample capability, enhanced hybridization signals, and reduced assay
time. In this thesis, line arrays of DNA probes were printed on a glass chip
through the microfluidic method. Target microchannels orthogonally intersected
with these line arrays, and complementary DNA molecules, upon hybridization,
were retained at the intersections as rectangular spots. Detection was achieved
through the read-out of the fluorescent labels on the targets. The high surface-to-
volume ratio in microchannels of nanolitre volume enhanced the detection
sensitivity as compared to that obtained with the bulk solution method. The spot
shape is more regular than that from the pin-spotted microarray, which is an
advantage for subsequent image processing. For diagnostic purposes, PCR
products amplified from the genomic DNA of fungal pathogens were detected
with this microfluidic intersection method. Moreover, with the aid of gold
nanoparticles, two 260-bp DNA sequences with single base-pair difference were
discriminated from each other at room temperature for the first time. In addition to
the pressure-driven flows used in rectangular chips, a centrifugal-pumping
method was employed to drive liquid movement in a CD-like microchip.
Connections from electrodes or tubing were avoided, resulting in the ease of
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conducting parallel hybridizations in multi-channels. For example, up to 100
samples can be analysed simultaneously with the CD-like microchip. The
centrifugal-pumping flow in the spiral channel was modeled mathematically and
simulated numerically by the computational flow dynamics (CFD) method. It was
found that the mathematical results and simulation results are consistent with the
experimental findings. Other than the flow study, the kinetics of microfluidic DNA
hybridization was also studied and simulated. The effects of probe coverage,
channel depths, assay conditions, and sample delivery rate on DNA hybridization
were investigated. The variation of signal intensity inside a hybridization spot and
from spots to spots was also discussed and compared with the experimental
findings. The proposed method provides a way to optimize both chip design and
experimental conditions during surface-based biosensor assays.
Keywords: Microfluidic DNA microarray; Centrifugal pumping; DNA diagnostics; Fungal DNA; Single-base-pair-mismatch discrimination; Gold nanoparticle; Spiral channel; Computational flow dynamics; Surface reaction kinetics.
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DEDICATION
This thesis is dedicated to my dear parents, Yuchun, and Chelsea, without
whom it would never have been accomplished.
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ACKNOWLEDGEMENTS
I would like to thank my thesis advisor, Dr. Paul C. H. Li, for his support
and guidance. He has been patiently teaching me the craft and art of scientific
research in the past years. I will never forget the enjoyable experience of
conducting microfluidic research in his laboratory. In the process, his integrity, his
respect for his student's scientific liberty, and his constant encouragement have
filled me with admiration.
I deeply appreciate the inspiration and the valuable advice from the other
members of my supervisory committee – Dr. George Agnes and Dr. Peter
Wilson. Their comments on various aspects of my thesis have kept me thinking
critically on the experimental design and results. I would also like to thank Dr.
Mary-Catherine Kropinski for training me on fluid dynamics. Her support has
been my principal sources on all matters in mathematics.
I am very grateful for the kind help from Dr. William S. Davidson and his
group. I specially thank Kryztoff Lubiensky and Yvonne Lai for training me the
molecular biology techniques. I am also indebted to Dr. Dipankar Sen and his
group for the access to laboratory equipment and resources such as the confocal
laser fluorescent scanner. Besides, I deeply appreciate the valuable advice on
my project provided by Dr. Hua-Zhong (Hogan) Yu.
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My thanks belong also to the members of our lab, both past and present.
The excellent work of Dr. Xing Yue Peng has been the ground of my PhD
program. I want to thank Dr. Te-Chun Wu for the help on microchip fabrication,
Dr. Hong Chen for his enlightening discussions on numerical simulation.
Besides, I would also like to thank Samar Haroun and Jonathan Lee for the
proofreading, Dr. Xiujun Li, Wei Xiao, Jacky Chou, Yuchun Chen, Michael Wong,
Iryna Kolesnyk, Katrina Smyth, Abootaleb Sedighi, and Zara Sanei for their
supportive work and comments on my experimental results. I am also grateful to
Carol Koch of Agriculture and Agri-Food Canada for kindly providing the genomic
samples of plant pathogens.
For the final stages of my PhD study, I specially thank Yuchun Chen for
providing me with love and encouragement. Despite long distance between us,
my parents and my sister have always supported me in whatever and wherever I
decided to do and to go, therefore, I feel very obligated to them.
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TABLE OF CONTENTS
Approval .......................................................................................................................... ii Abstract .......................................................................................................................... iii Dedication ....................................................................................................................... v Acknowledgements ........................................................................................................ vi Table of Contents .......................................................................................................... viii List of Figures ................................................................................................................ xii List of Tables .............................................................................................................. xxvii List of Abbreviations .................................................................................................. xxviii List of Symbols ............................................................................................................ xxxi
1: Introduction ............................................................................................................... 1 1.1 Fundamentals of DNA microarray hybridization....................................................... 1
1.1.1 The building blocks of DNA .......................................................................... 1 1.1.2 DNA duplex structure ................................................................................... 2 1.1.3 DNA hybridization analysis .......................................................................... 3 1.1.4 Hybridization of mismatched DNA sequences ............................................. 8 1.1.5 DNA microarray and its applications .......................................................... 11
1.2 Introduction to microfluidic DNA microarray technologies ...................................... 14 1.2.1 DNA hybridization in microfluidic chambers ............................................... 16 1.2.2 Microfluidic DNA hybridization with low-density probe arrays ..................... 23 1.2.3 Microfluidic DNA microarray using centrifugal pumping ............................. 31
1.3 Research outlines ................................................................................................. 38 1.4 Dissertation structure ............................................................................................ 39
2: Microchip Fabrication and Detection Instrumentation ......................................... 43 2.1 Introduction ........................................................................................................... 43 2.2 PDMS-based Microfabrication Processes ............................................................. 45
2.2.1 Surface preparation and layer deposition processes.................................. 47 2.2.2 Photolithography processes ....................................................................... 49 2.2.3 Casting and bonding processes ................................................................. 51 2.2.4 Comparison of molding master made from SU8 or wet etching ................. 53
2.3 Surface modification to generate aldehyde-functionalized glass chips. ................. 56 2.4 Immobilization of probe DNA. ................................................................................ 58 2.5 Quantification of fluorescent image and data analysis ........................................... 59
3: Flexible Microarray Construction and Fast DNA Hybridization Conducted on a Microfluidic Chip for Greenhouse Plant Fungal Pathogen Detection ............. 60 3.1 Introduction ........................................................................................................... 60 3.2 Experimental ......................................................................................................... 63
3.2.1 Materials. ................................................................................................... 63
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3.2.2 Fabrication of PDMS channel plates. ......................................................... 66 3.2.3 Probe line printing, sample hybridization and result read-out by
fluorescent scanning. ................................................................................. 67 3.3 Results and discussion .......................................................................................... 69
3.3.1 Flexible probe immobilization without spotting. .......................................... 69 3.3.2 Fast hybridization of multiple DNA samples. .............................................. 73 3.3.3 Effect of probe tether length and one-base-pair-difference
discrimination. ............................................................................................ 76 3.4 Conclusion ............................................................................................................ 80
4: Gold Nanoparticle-assisted Single Base-Pair Mismatch Discrimination on A Microfluidic Microarray Device ............................................................................... 81 4.1 Introduction ........................................................................................................... 81 4.2 Experimental ......................................................................................................... 83
4.2.1 Fabrication of the PDMS-glass microchip. ................................................. 83 4.2.2 DNA samples ............................................................................................. 83 4.2.3 Depositing GNP layers on glass surface using microfluidic method. .......... 84 4.2.4 Preparation of DNA-GNPs conjugates. ...................................................... 84 4.2.5 Probe line printing, sample hybridization and result read-out by
fluorescent scanning. ................................................................................. 85 4.3 Results and discussion .......................................................................................... 85
4.3.1 GNP-modified surface and its application to microarray DNA hybridization .............................................................................................. 85
4.3.2 GNP-DNA conjugates and its application to single-base-pair discrimination ............................................................................................. 90
4.4 Conclusion ............................................................................................................ 95
5: Fungal Pathogenic Nucleic Acid Detection Achieved with a CD-like Microfluidic Microarray Device ................................................................................... 96 5.1 Introduction ........................................................................................................... 96 5.2 Experimental ......................................................................................................... 98
5.2.1 Materials .................................................................................................... 98 5.2.2 Surface modification of glass chips and the fabrication of PDMS
channel plates ........................................................................................... 98 5.2.3 Probe line array creation ............................................................................ 99 5.2.4 Sample hybridization with spiral channel plate assembly ......................... 100 5.2.5 Quantification of fluorescent image and data analysis ............................. 101
5.3 Results and discussion ........................................................................................ 101 5.3.1 Improvements in the design and fabrication of channel plates ................. 101 5.3.2 Hybridization of oligonucleotide samples on the CD-like MMA ................. 102 5.3.3 Hybridization of PCR products on CD-like MMA ...................................... 105 5.3.4 Hybridization specificity on CD-like MMA ................................................. 107
5.4 Conclusions ........................................................................................................ 110
6: Optimization of a CD-like Microfluidic Microarray Device for the Fast Discrimination of Fungal Pathogenic DNA .............................................................. 111 6.1 Introduction ......................................................................................................... 111 6.2 Experimental ....................................................................................................... 113
6.2.1 Fabrication of microfluidic devices. .......................................................... 113
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6.2.2 Oligonucelotides and the preparation of fungal pathogenic DNA samples. .................................................................................................. 113
6.2.3 Sample hybridization and fluorescent detection. ...................................... 114 6.3 Results and discussion ........................................................................................ 116
6.3.1 Fast and parallel hybridization using continuous centrifugal flow. ............ 116 6.3.2 Enhanced sensitivity by the control of flow, channel depth and
temperature. ............................................................................................ 119 6.3.3 Enhanced detection sensitivity due to the use of Cy5 dye labels. ............ 122 6.3.4 Discrimination of PCR products with single base-pair difference. ............. 125
6.4 Conclusion .......................................................................................................... 128
7: Analysis and Modeling of Flow in Rotating Spiral Microchannels: Towards Math-aided Design of Microfluidic Systems Using Centrifugal Pumping ..................................................................................................................... 129 7.1 Introduction ......................................................................................................... 129 7.2 Chip design, microfabrication and flow measurement of the spiral
microchannels ..................................................................................................... 133 7.3 The mathematical model ..................................................................................... 134 7.4 Numerical simulation of the microflow ................................................................. 139 7.5 Results and discussions ...................................................................................... 141
7.5.1 Characterization of microflows in equiforce spiral channels with experimental data .................................................................................... 141
7.5.2 Comparison of solutions from the mathematical model with the experimental data. ................................................................................... 143
7.5.3 Validation of the assumptions in the mathematical modeling with the experimental data and simulation results ................................................. 146
7.6 Conclusions ........................................................................................................ 155 7.7 Appendix A: The spiral coordinate system ........................................................... 157 7.8 Appendix B: Simulation set-up and the study on the transversal flow with the
CFD program ...................................................................................................... 161 7.8.1 Governing equations ................................................................................ 161 7.8.2 Volume, boundary, and initial conditions in the numerical simulations ..... 162 7.8.3 The effect of mesh grid density on the computation time and
accuracy during the numerical simulations .............................................. 164 7.8.4 Validation of the assumption of negligible cross-channel flows. ............... 166
8: Modeling of Microfluidic DNA Microarray Hybridization and Its Applications to Experimental Optimization ............................................................. 168 8.1 Introduction ......................................................................................................... 168 8.2 Experimental ....................................................................................................... 171 8.3 Model construction for microfluidic DNA microarray hybridization ....................... 171
8.3.1 Navier-Stokes and continuity equations ................................................... 171 8.3.2 Mass transport and hybridization kinetics ................................................ 174 8.3.3 Non-dimensionalization of the reaction-diffusion and kinetic
equations. ................................................................................................ 179 8.3.4 Physical interpretation of the dimensionless numbers: ............................. 181
8.4 Simulation of microfluidic DNA microarray hybridization ...................................... 184 8.4.1 Numerical simulation with COMSOL program .......................................... 184
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8.4.2 Parameter values used during simulation ................................................ 185 8.5 Results and discussion ........................................................................................ 189
8.5.1 Bulk concentration profiles of static hybridization and microfluidic hybridization ............................................................................................ 189
8.5.2 Prediction of the detectable range of oligonucleotide targets ................... 190 8.5.3 Effects of flow rates and channel dimensions on hybridization signals ..... 192 8.5.4 Effect of probe coverage on hybridization signals .................................... 198 8.5.5 Assay conditions on the improvement of signal intensity and
specificity/selectivity ................................................................................. 201 8.5.6 Spot morphology ..................................................................................... 210 8.5.7 Signal variation from spot to spot ............................................................. 217
8.6 Conclusions ........................................................................................................ 221
9: Conclusions and Perspectives ............................................................................ 222 9.1 Concluding remarks ............................................................................................ 222
9.1.1 Microfluidic surface hybridization ............................................................. 223 9.1.2 Applications and modeling of the CD-like chip using centrifugal
pumping flow ........................................................................................... 223 9.1.3 Modeling and simulation of microfluidic hybridization kinetics. ................. 224
9.2 Outlook and research perspective ....................................................................... 225 9.2.1 Sensitivity ................................................................................................ 225 9.2.2 Selectivity ................................................................................................ 226 9.2.3 Integration and packaging. ....................................................................... 226 9.2.4 Modeling and simulation of centrifugal-pumping flows ............................. 227 9.2.5 Modeling and simulation of hybridization kinetics ..................................... 227
10: Appendix .............................................................................................................. 231 10.1 COMSOL simulation steps for the kinetics study of microfluidic microarray
hybridization ........................................................................................................ 231 10.1.1 Channel geometry construction ............................................................... 232 10.1.2 Choosing the physics models: ................................................................. 233 10.1.3 Domain Coupling: .................................................................................... 234 10.1.4 Constant and Variable Specifications ...................................................... 235 10.1.5 Subdomain equation settings: .................................................................. 239 10.1.6 Boundary conditions settings: .................................................................. 241 10.1.7 Meshing ................................................................................................... 242 10.1.8 Solver Parameters and Solver Manager .................................................. 243 10.1.9 Post-processing and visualization ............................................................ 244
Reference List ........................................................................................................... 245
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LIST OF FIGURES
Figure 1-1 (a) General structure of the nucleotide. The nitrogenous base and the pentose sugar are linked each other through N-glycosidic linkage. The official numbering system is also shown. (b) The two purine nitrogenous bases in DNA. (c) The two pyrimidine nitrogenous bases in DNA. ........................................................................................................... 1
Figure 1-2 (a) Watson-Crick model of a 21-bp DNA double-helix. The pentose-phosphate backbones of the two strands (shown in blue and red ribbons) form a right-handed double helix. The DNA structure was generated with the DNA modeling server by Vlahovicek et al. [2]. Image visualization was performed with the Chimera molecular modeling system [3]. (b) Chemical structure of the specific hydrogen bonding in a DNA duplex. The duplex is stabilized by hydrogen bonding between complementary base pairs and (though not obvious from this drawing) by base stacking interactions between adjacent base pairs. ...................................................................................................... 2
Figure 1-3 Schematic view of the DNA hybridization process. (a) Two complementary single-stranded DNA before hybridization. (b) Intermediate state with a few base pairs from strand collision. (c) Hybridized DNA duplex from zippering step. ................................................... 4
Figure 1-4 (a) Preparation of DNA targets from genomic DNA. Here, the genomic DNA duplexes are denatured to two single strands. One of the strands (highlighted in yellow color) are then amplified and labeled with proper tags for later hybridization analysis. (b) and (c) show the two formats of DNA hybridization analysis: (b) Target DNA is labeled. (c) Probe DNA is labeled. ................................................................................ 7
Figure 1-5 (a) Distorted DNA duplex structure from two T·G mismatches in the center. The two green arrows indicate the two T·G mismatches. (b) The sequence of the duplex shown in (a). The blue strand is 5'-CGCATTACGC-3', and the red one is 5'-GCGTGGTGCG-3'. (PDB access number: 1SNH [24]) ............................................................................ 8
Figure 1-6 Hybridization-based approaches for the discrimination of SNP sequences. (a) Targets are prepared from two SNP sequences with only one base-pair difference. (b) Fluorescence-labeled targets hybridize to probe molecules. The mismatched sequences form unstable duplexes. (c) The unstable MM duplexes are denatured and removed by high-stringency washing conditions. (d) Fluorescence signals from retained PM duplexes. .............................................................. 10
Figure 1-7 Hybridization assay with spotted probe microarray. (a) Microarray probe spotting pins used in a commercial microarrayer. The photo is
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adapted from the product datasheet of SpotBot® Titan High-Capacity microarrayer. (b) Glass slide with chemically-modified surface ready for probe binding. The slide can be labeled with barcode for easy identification. (b) Microspotting probe molecules on the slide. The lower image shows surface tethered probe sequences. The individual probe sequences can be identified by the position of the corresponding feature on the regular microarray grid. (c) Hybridization. Target solutions are applied to the slide and are incubated in a heated humidified box. Labeled targets can freely diffuse over the microarray surface until they hybridize with a complementary probe (lower image). (d) Washing step. After hybridization, unbound targets are washed away with buffer solutions as shown in the lower image. (e) Microarray image analysis. Quantification of the surface bound targets is performed by measuring the fluorescence intensity of the hybridization spots using a fluorescence scanner. ............................................................. 13
Figure 1-8 (a) Diagram for sample recirculation system on the hybridization chamber. (b) Hybridization image of fluorescence-labelled target nucleotide with 0.1 mL·min-1 continuous recirculating flow on a DNA microarray for 40 min. Reproduced from [73] by permission of The Royal Society of Chemistry. (c) Chaotic mixing of the dye solutions in two PDMS microfluidic chambers facilitated by the herringbone indentations in the bridge channel. (d) Signal improvement by microfluidic mixing on a home-spotted microarray. Top: Dynamic; Bottom: static hybridization. Reprinted with permission from [74], Copyright © 2006 John Wiley & Sons, Inc. .................................................... 18
Figure 1-9 (a) Schematic showing a number of air bubbles in the top layer of the DNA biochip chamber. An energetic cavitation streaming motion created by the PZT transducer was observed in the vicinity of each bubble. (b) Top image: fluorescence image of a biochip after 2-h static hybridization; Bottom image: fluorescence image of a biochip after 2-h hybridization aided with cavitation microstreaming. Reprinted with permission from [79], Copyright © 2003 American Chemical Society. ........... 20
Figure 1-10 (a) Illustration of the coordinated pump and valve used for dynamic hybridization. Fluids are extracted and reinjected to the hybridization chamber under a protocol to induce chaotic movement inside the chamber. (b) Photographs of dye solution mixing in the hybridization chamber after 2 cycles of liquid removal and reinjection processes using a 30-µL stroke volume. The dye distribution appears to be homogeneous after 16 cycles. Reprinted with permission from [80], Copyright © 2004 Elsevier Ltd. ...................................................................... 20
Figure 1-11 (a) Schematic drawing of a straight hybridization channel and probe spots (unit: mm). The flow direction was from top to bottom. (b) Fluorescent images after 30 min hybridization. Left: hybridization results at u = 1 cm·s-1; right: hybridization results at u = 0 cm·s-1 (control). (c) Comparison of the averaged fluorescence intensities after hybridization. Reproduced from [87] by permission of The Royal Society of Chemistry. .................................................................................... 25
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Figure 1-12 (a) An illustration showing scrambled discrete plugs being swept over probe rows in the serpentine channel. The black arrow denotes the shuttle flow inside the microchannel. (b) The fluorescence images are from 500-s microfluidic hybridization (top row), 500-s static hybridization (center row) or 2-h static hybridization (bottom row). The left column represents the results from 20-mer PM targets, and the right column represents the results from 20-mer MM targets with single base-pair mismatch in sequence center. Reprinted with permission from [90], Copyright © 2005 Oxford University Press. ................................... 25
Figure 1-13 (a) Fluorescent image of the hybridization of DNA probes (5 and 10 µM) spotted on activated glass slides with increasing concentration of DMSO. Reprinted with permission from [112], Copyright © 2003 Oxford University Press. (b) Fluorescence images acquired in Cy3 (green) and Cy5 (red) channels show the parallel microfluidic patterning of multiple DNA probes. Reprinted with permission from [128], Copyright © 2009 American Chemical Society. (c) A 16-channel microfluidic network was used to pattern 20-µm lines of decreasing antigen coverage onto a PDMS substrate (left line to right line) using solutions of different concentrations. The antigen was labelled with rhodamine. Reprinted with permission from [120], Copyright © 2000 American Chemical Society. (d) Cross-polarized optical image of [Mo3Se3
-]∞ nanowire patterns on glass substrate made with microchannel networks. Reprinted with permission from [131], Copyright © 2000 American Chemical Society. ............................................. 28
Figure 1-14 (a) Intersection approach for performing an immunoassay on a surface with microfluidic network. (i) Patterning different antigen molecules along the horizontal lines on a solid substrate. (ii) The area of the substrate left unpatterned during step (i) is blocked with bovine serum albumin (BSA) to prevent nonspecific binding in subsequent steps. (iii) Antibodies flowing through the channels of a second microfluidic network locally bind to the patterned antigens. (iv) Reading the rectangular binding patches reveals the amount of antibodies present in the samples. Reprinted with permission from [124], Copyright © 2001 American Chemical Society. (b) SPR difference images showing hybridization of a RNA sample onto an array of surface-bound probe DNA. Hybridization of the target RNA onto the probe DNA array was indicated by a change in the reflectivity. Reprinted with permission from [96], Copyright © 2001 American Chemical Society. ......................................................................................... 30
Figure 1-15 (a) Photograph of the microfluidic chip containing shuttle-flow channels, microvalves and micropumps. The entire chip consists of three layers, the top and middle layer were made of PDMS containing microvalves, micropumps, and shuttle flow channels; the bottom layer was a glass substrate with gel pads on which DNA probes were immobilized. The shuttle flow hybridization was realized by controlling the gas ports 1, 2 and 3 automatically. (b) Hybridization specificity assay using four serotypes of the Dengue virus under shuttle flow conditions (frequency 2 Hz). Channels 1 to 4 indicated target DNAs (200 nM) of serotypes I to IV, with repetitions in channels 5 to 8,
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respectively. The duration of hybridization process was 90 s and washing time was 30 s. Reproduced from [64] by permission of The Royal Society of Chemistry. .......................................................................... 32
Figure 1-16 (a) Schematic representation of a CD microfluidic device sealed with a glass substrate for DNA hybridization. It consists of a PDMS CD slab containing twelve DNA hybridization assay units with immobilized DNA probe arrays. (b) Schematic diagram of a single DNA hybridization assay unit. (c) Hybridization specificity tests with the CD microfluidic device. Top: Dengue virus serotype 1 targets. Bottom: Dengue virus serotype 2 targets. The CD device was rotated at 22 Hz for 3 s and then stopped for 3 s during the reciprocating process, with a duration of 90 s. Reprinted with permission from [108], Copyright © 2009 Elsevier Ltd. .................................................................................................. 36
Figure 1-17 The organization structure of this dissertation. .......................................... 42
Figure 2-1 Sequence for fabrication of the microfluidic assembly using negative photoresist SU-8. (a) a plain silicon wafer (b) Si wafer coated with photoresist film; (c) wafer exposed to UV light through a photomask; (d) photoresist developed; (e) PDMS prepolymer solution casted on the SU-8 master; (f) PDMS channel plate peeled off; (g) PDMS channel plate bound to a glass chip to produce assembly. ............................ 46
Figure 2-2 Photograph of the softwall clean room facilities used for making microchip and a bionocular microscope for surface examination. .................. 47
Figure 2-3 (a)-(d) Illustration of the spin coating processes for the creation of the SU8 photoresist layer on a silicon wafer. (e) a spin coater with controller (f) rotation speed versus the thickness of the SU8 resin layer. The figure is adapted from MicroChem® product datasheet. SU8-50 and SU8-100 are different from each other in viscosity for different applications. In this thesis, SU8-50 has been used throughout. ....... 49
Figure 2-4 (a) Silicon wafer aligned with photomask under UV irradiation; (b) SU8 layer with microstructures on a 5-inch silicon wafer after the developing process. ...................................................................................... 50
Figure 2-5 Comparison of the quality of PDMS microchannels fabricated from two photomasks of different printing resolutions. (a) Photomask printed with 3368 dpi. (b) The microscopic image of the PDMS channel plate made from (a). (c) Photomask printed with 20,000 dpi. (d) The microscopic image of the PDMS channel plate made from (c)....................... 51
Figure 2-6 (a) SU8 master with weir structure around the wafer for PDMS molding. (b) Assembly of the PDMS microchannel plate with a glass disk. .............................................................................................................. 53
Figure 2-7 Sequence for fabrication of the microfluidic assembly using a positive photoresist and subsequent HF etching. (a) A clean Si or glass wafer. (b) Cr and Au masked Si wafer (c) The wafer in (b) is coated with positive photoresist. (d) The wafer in (c) is exposed to UV light through a photomask; (e) photoresist is removed; (f) The exposed metal mask is etched; (g) The exposed Si or glass etched; (h) The photoresist and metal is stripped; (i) PDMS prepolymer solution casted on the SU8
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master; (j) The cured PDMS channel plate is peeled off; (k) PDMS channel plate is sealed to a glass chip to produce assembly. ....................... 54
Figure 2-8 Comparison of the Si masters and microchannels fabricated using positive and negative photoresist. (a) The reflective microscope image of the Si master fabricated from positive photoresist followed with KOH etching. (b) Surface profile of the microchannels in (a); (c) The reflective microscope image of the Si master fabricated from SU8 photoresist. (d) Surface profile of the microchannels in (c). ........................... 56
Figure 2-9 Surface modification to generate aldehyde-functionalized glass surface. Reprinted with permission from [94], Copyright © 2007 American Chemical Society. ......................................................................... 57
Figure 2-10 Covalent attachment of aminated probe DNA to aldehyde glass surface. Reprinted with permission from [94], Copyright © 2007 American Chemical Society. ......................................................................... 58
Figure 2-11 Typhoon 9410 confocal laser fluorescent scanner. ..................................... 59
Figure 3-1 The microfluidic microarray method using straight microchannels. (a) The creation of a DNA probe line array on an aldehyde-modified glass slide via straight microchannels. (b) The hybridization of DNA samples in straight channels orthogonal to the straight probe lines printed on the glass slide. Reprinted with permission from [94], Copyright © 2007 American Chemical Society. ......................................................................... 63
Figure 3-2 The images of the assembly of a 2"×2" PDMS channel plate on a 3"×2" glass slide. (a) Image of16 channels filled with blue-dye solutions in horizontal direction. (b) Image of 16 channels filled with green-dye solutions in vertical direction. Reprinted with permission from [94], Copyright © 2007 American Chemical Society. ............................................. 66
Figure 3-3 Microfluidic hybridization of target DNA strands (in red) in the parabolic liquid front to the probe DNA strands (in blue) immobilized on the glass chip surface. Reprinted with permission from [94], Copyright © 2007 American Chemical Society. ............................................................. 68
Figure 3-4 Probe immobilization. (a) Effect of ionic strength of spotting solutions and immobilization time on the ADF signal. The probe line arrays were made by incubating 0.8 µL of 25-µM ADF prepared in 1.0M NaCl (grey bar) or 0.1M NaCl (white bar) in microchannels at different durations. The slide was chemically reduced and then washed with distilled water. The fluorescent signals were measured by scanning the slide at 488nm. (b) The fluorescent image of ADF probe lines (vertical green stripes) printed on the glass slide using different immobilization times. The brighter the probe lines, the stronger the fluorescent signals. Reprinted with permission from [94], Copyright © 2007 American Chemical Society. ......................................................................................... 70
Figure 3-5 Sample hybridization. (a) The immobilization signal of various ADF probe solutions (0.8-µL) at different concentrations (10 to 400 µM) that were incubated in microchannels for 2 h. After washing, the slide was scanned at 488nm. (b) The hybridization signals resulted from the above probe lines. Complementary oligonucleotides (CD’) labelled with
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Cy5 (100 nM, prepared in 1xSSC + 0.2%SDS) was hybridized to the ADF probe lines for 10 min. After washing, the slide was scanned at 633nm. (c) Overlaid dual-channel image of the same glass slide showing both printed probe lines (vertical green lines) and square hybridization patches (red) at intersections. ADF probe immobilization was achieved in duplicate at each concentration. Reprinted with permission from [94], Copyright © 2007 American Chemical Society. ........... 71
Figure 3-6 Hybridization of oligonucleotide samples to printed probe lines. (a) Fluorescent images of the hybridizations of oligonulceotides (FB’ and FD’ prepared in 1X SSC + 0.2% SDS) with probe line arrays for 10 min at room temperature. (b) Histogram showing the fluorescent intensities of hybridization versus non-specific binding at various sample concentrations. The grey bars represent the signals of samples hybridized with their complementary probe sequences, i.e., FB’ with AB, or FD’ with AD; the white bars represent the non-specific binding. The error bars describe the standard deviations of the signals from 5 or 7 hybridization patches. Reprinted with permission from [94], Copyright © 2007 American Chemical Society. ............................................. 74
Figure 3-7 Hybridization of PCR products to printed probe lines. (a) Fluorescent signals from the hybridization of 2.6-ng pre-denatured PCR products (FB’P and FD’P) at 50 ºC for 5-min flow, 30 min incubation and overnight incubation, respectively. (b) The fluorescent images corresponding to the left histogram of hybridizations of 2 samples to 7 probe lines. Reprinted with permission from [94], Copyright © 2007 American Chemical Society. ......................................................................... 76
Figure 3-8 The immobilized oligonucleotide probe with C6 or C12 tether as spaced from the glass substrate. Reprinted with permission from [94], Copyright © 2007 American Chemical Society. ............................................. 77
Figure 3-9 Hybridization of PCR products to probes having different tether lengths. (a) Fluorescent signals from hybridization of PCR products (1.4 ng and 2.6 ng) to probes with 2 different tether lengths. (b) The fluorescent image corresponding to the left histogram of hybridizations of samples to 5 probe lines. (c) Effect of probe tether length on discrimination of PCR products with one-base-pair-difference. Fluorescent signals come from the fluorescent patches of three PCR products (FB’P, FBN’P and FD’P, 1.4ng for each). The small black bars come from the non-specific binding signals of FD’P and they are too low to be seen on probe AB. The error bars describe the standard deviations of the signals from 5 duplicated tests. (d) The fluorescent image corresponding to the left histogram of hybridizations of 3 samples to 5 probe lines. In all cases, the DNA targets were hybridized by continuous-flow method for 5 min at 50 ºC. Reprinted with permission from [94], Copyright © 2007 American Chemical Society. ........... 78
Figure 4-1 Schematic diagram of the formation of the nanoscale-controlled spacing between oligonucleotide probes using GNPs. (a) Protonated amine groups on the APTES-treated glass surface. (b) GNPs, with adsorbed citrate ions, are then deposited to the aminated glass surface and form a submonolayer. (c) The remaining non-reacted
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amine groups are deprotonated using a pH 11 buffer and masked by acetic anhydride (Ac2O). (d) When oligonucleotides probe DNA solutions flow through the submonolayer, the amine groups at the 5’-end of the molecules will bind only to GNPs which are well spaced out on the glass surface. Reprinted with permission from [95], Copyright © 2010 American Institute of Physics. .............................................................. 87
Figure 4-2 Different modified surfaces for hybridization experiments. (a) Image of an APTES modified glass slide with immobilized GNP strips (b) Magnified image of the glass slide with insets showing (i) Flow through 2-µL GNP solutions, (ii) Flow through 10-µL GNP solutions. The glass slide was first treated with APTES solution to create an aminated surface. Then a PDMS channel plate was sealed against the glass slide. GNP solutions in different amounts were filled through 8 microchannels. The deposition of GNPs onto the aminated surface resulted in the pink strips. The rest of the microchannels were left empty to keep the glass surface aminated. The images were taken after washing the microchannels and peeling off the PDMS plate. Reprinted with permission from [95], Copyright © 2010 American Institute of Physics. ....................................................................................... 88
Figure 4-3 Fluorescent images of the hybridization results from (a) 21-mer and (b) 50-mer target oligonucleotides at different modified surfaces. The targets are either complementary perfect- match (PM) or one-base mismatch (MM) in the sequence center with the probe DNA molecules. (a) Hybridization of Cy5 labelled 21-mer targets. The probe DNA lines were printed microfluidically on: aminated glass surface, on surface modified by flowing through 2-µL GNP solutions, and on surface modified by flowing through 10-µL GNP solutions (b) Hybridization of Cy5 labelled 50-mer targets. The probe DNA lines were printed microfluidically on: aminated glass surface, on GNP modified surface with Ac2O treatment to cap remaining amine groups, and on GNP modified surface without AC2O treatment. Reprinted with permission from [95], Copyright © 2010 American Institute of Physics. ........................... 89
Figure 4-4 (a) GNP-DNA conjugates from the incubation of target DNAs with gold nanoparticles. (b) Perfectly matched target DNAs desorbed from GNPs and hybridized to the surface immobilized probes. (c) Mismatched DNAs remained bound to GNPs and were washed away through microfluidic method. Reprinted with permission from [95], Copyright © 2010 American Institute of Physics. ........................................... 91
Figure 4-5 (a) Images of hybridized patches of perfect-matched (PM) and mismatched (MM) target oligonucleotides in triplicate. Here, the oligonucleotides were pre-incubated with GNPs (5 nm) at different ratios. (b) Discrimination ratios between PM and MM duplexes. The discrimination ratios were calculated by dividing the signal of PM DNAs with that of MM DNAs (The higher ratio, the better). (c) The fluorescent hybridization signals from the images in (a), and the results at Oligo/GNPs = 1:1 are expanded and shown in the right inset. Reprinted with permission from [95], Copyright © 2010 American Institute of Physics. ....................................................................................... 92
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Figure 4-6 (a) Images of hybridized patches of perfect-matched (PM) and mismatched (MM) PCR products in triplicate. Here, the amplicons were pre-incubated with GNPs (5 nm) at different ratios. (b) Discrimination ratios between PM and MM amplicons. The discrimination ratios were calculated by dividing the signal of PM DNAs with that of MM DNAs (The higher the ratio, the better). Reprinted with permission from [95], Copyright © 2010 American Institute of Physics. ......... 94
Figure 5-1 Assemblies of the PDMS channel plates with glass disks. (a) The circular channel plate with radial microchannels. All the channels (100 in total) were filled with dye solutions; (b) The image of an equi-force spiral channel plate assembled with a glass disk. Here, 30 out of 100 spiral microchannels, three in a group, were filled with dye solutions. The scale bar represents 10 mm. .................................................................. 99
Figure 5-2 Schematic diagram of probe immobilization and sample hybridization using CD-like microfluidic microarray assemblies. (a) Probe printing procedure: an array of radial probe lines was created on an aldehyde-modified glass disk using a radial channel plate. (b) Hybridization procedure: the hybridization occurring at the intersections between the spiral channels and radial probe lines, shown as colored patches in the last circle. Reprinted with permission from [134], Copyright © 2010 Elsevier Ltd. ................................................................................................ 100
Figure 5-3 DNA hybridization on a CD-like glass chip. (a) The schematic diagram of hybridization patches formed at the intersections between 6 sample channels and 3 probe lines. (b) The fluorescent image of the entire glass disk. The 3 straight traces are resulted from the radial flow of the fluorescent marker during probe immobilization. The 3 grey spiral traces are resulted from the spiral flows of marker during sample hybridization. Hybridization results obtained in the rectangular region are expanded to give the middle inset. The right inset shows the groups of rectangular patches formed near the disk center, which are resulted from the hybridization of different concentrations of oligonucleotide samples with their complementary probe lines. The probe lines (AD or AB) were created by 40 min-incubation of 25-µM aminated oligonucleotide probes in the radial channels. Oligonucleotides hybridizations were achieved at room temperature in 3-min spinning at 700 rpm, and then dried out at 3600 rpm. Reprinted with permission from [129], Copyright © 2008 Elsevier Ltd. ......................... 103
Figure 5-4 (a) The calibration graph of the hybridization signals from oligonucleotide FB’ (top curve) and FD’ (bottom curve). (b) The hybridization signals of FB’ samples using different solution concentrations and volumes. In all cases, the samples were hybridized to 25-μM probe lines at room temperature for 10 min and the error bars describe the standard deviations of the signals from 9 hybridization patches. The fluorescent intensities expressed have already been subtracted from the background. Reprinted with permission from [129], Copyright © 2008 Elsevier Ltd. .................................................................... 105
Figure 5-5 (a) Comparison of different flow conditions for the hybridization of oligonucleotides and PCR products at 45 ºC. From left to right the
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hybridization conditions were: oligonucleotide samples (FD’, solid bar) by continuous flow for 5 min, PCR products (FD’P, hatched bar) by continuous flow for 10 min, or by stop-flow incubation for 10, 30, 60 and 120 min. For continuous flow, the spun rate was 500 rpm; whereas for stop-flow incubation, the samples were first introduced at a spun rate of 700 rpm for 2 min. For oligonucleotide sample, 5-nM FD’ was used because it already gave sufficiently high intensity; for PCR products, 20-nM FD’P was used, but the signal for 10-min stop-flow hybridization of FD’P was not detected and the variation of background was shown instead. The error bars describe the standard deviations of the signals from 9 hybridization patches. (b) The effects of time and temperature on the hybridization of PCR products. FD’P (20 nM) was introduced into spiral channels by spinning at 700rpm for 2min followed by incubation in an oven for different times at different temperatures. Reprinted with permission from [129], Copyright © 2008 Elsevier Ltd. ................................................................................................ 106
Figure 5-6 The hybridization specificity shown by the plots of fluorescent intensities versus locations in the spiral channels. The samples are fluorescein-labelled oligonucleotide (FD’) and PCR products (FD’P), each at 2 concentrations. (a) The samples flow from left to right intersecting the AB and AD probe lines alternatively. (b) The samples flow from left to right intersecting various probe lines in this sequence: AD, 7 non-complementary probe lines, AB, 7 non-complementary probe lines, and AD, as depicted in the box as D, N, B, N and D, respectively. (c) The fluorescent images correspond to the hybridizations and backgrounds shown in (b). All the probe lines were created by 40 min-incubation of 25 μM aminated oligonucleotide probe. Oligonucleotide sample hybridizations were achieved by 3-min spinning and dry-out at room temperature. For PCR products, they were firstly introduced into channels by spinning and then incubated in oven at 45°C. After hybridization for 2 hours, the DNA sample solutions inside channels were spun out at 3600rpm. Reprinted with permission from [129], Copyright © 2008 Elsevier Ltd. ................................ 108
Figure 6-1 Comparison between the continuous-flow and stop-flow methods of hybridization. (a) The fluorescent images show the PCR product hybridizations conducted with two different flow methods at 42 ºC. The dark rectangular patches represent the specific binding of the complementary targets. 1.0 μL of PCR products (CB’P or CD’P) were applied to the spiral microchannels. Probe AB was used to print radial probe lines (b) Line graph showing the average fluorescent intensities along the bottom radial probe line intersected with 20 spiral sample channels depicted in (a). (c) Hybridization signal comparison of two continuous-flow methods on same microchannel plate. Here, six groups of oligo probe AB were preprinted and distributed evenly on a glass disk as shown in the inset. Sample solutions (0.2ng CB’P in 2.5xSSC+0.2%SDS), driven by either centrifugal force or vacuum suction, flowed through and intersected with these probe lines. Each bar represents signals from the average of nine hybridization patches. The bar number in the graph matches to the number as shown in the inset, indicating the position of hybridization along the spiral channels.
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The error bars represented the standard deviation of hybridization signals from the nine patches. The sample volume is 0.8 μL and the rotation speed or vacuum was controlled to ensure an average 3 min of hybridization time. (d) Picture of the broken liquid column (in red) inside a 24-μm depth microchannel during vacuum suction. The inset shows the magnified picture of the area. Reprinted with permission from [134], Copyright © 2010 Elsevier Ltd. .................................................. 118
Figure 6-2 Enhanced sensitivity due to smaller channel depth and higher temperature. (a) The bar graph showing the measured fluorescence intensities from the hybridization of 1.6-ng CB’P at different rotation speeds at room temperature. The line graph shows the corresponding residence times. The error bars were calculated from three measurements. (b) The effect of channel depth on hybridization signal intensity. Different amount of PCR products (CD’P) were hybridized at 42°C for 3 min. (c) Fluorescent intensities along an AB probe line. Ten samples (CB’P) were detected on the test disk at different concentrations and each sample was conducted in duplicate. From left to right, five samples (6.4, 3.2, 1.6, 0.8, and 0.2 ng) were first hybridized at room temperature (23°C) for 3 min. After dry-out of these channels, another group of 5 samples was hybridized at 42°C for 3 min. In all cases, the volume of sample solutions was 1.0 μL. The insets showed the magnified graphs of the hybridization signals of 0.2 ng CB’P. (d) Calibration curves of hybridization signals of PCR products (0.2~6.4 ng). The error bars represented the standard deviation of hybridization signals from six patches. Reprinted with permission from [134], Copyright © 2010 Elsevier Ltd. ................................ 121
Figure 6-3 Enhanced hybridization signals of Cy5-labelled oligonucleotides due to higher hybridization efficiency and less photobleaching. (a) signal-to-noise ratio from the hybridization of different labelled oligonucleotides with the same probe lines. The results of fluorescein-labelled DNA are expanded to give the right inset picture. Here, the concentration of both oligonucleotide samples is 0.1 μM. (b) Comparison of hybridization efficiency between Cy5-labelled and fluorescein-labelled oligonucleotides. The left two bars show the normalized fluorescent intensities from the hybridization of CD’ or CD’ + FD’ (scanned at 670nm). The right two bars show the normalized fluorescent intensities from the hybridization of FD’ or CD’ + FD’ (scanned at 532 nm). In all the cases, the final concentrations of different labelled oligonucleotides are 1 µM. (c) Photobleaching effect on different dye labelled oligonucleotides. Normalized fluorescent intensity from the chip with hybridized oligos at the specific wavelength of fluorescein dye. In all the cases, 1 µL of 0.1-µM oligo samples labelled with Cy5 or fluorescein dyes were applied and hybridized at room temperature for 45min in dark place. After removal of the channel plate, the glass chip was scanned consecutively for three times and it was then exposed to room light for 4 h before it was scanned for the fourth time. The error bars here represent the standard deviations of the hybridization signals of six patches. Reprinted with permission from [134], Copyright © 2010 Elsevier Ltd. .......................................................... 124
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Figure 6-4 Differentiation of Botrytis species with single-base-pair difference at various hybridization temperatures. (a) 4 groups of fluorescent images showing 9 patches of matched duplex and 9 patches of mismatched duplex. Each image was obtained from the hybridization of sample solutions in 3 spiral channels intersecting with 3 probe lines at the specified temperature. Two PCR products, perfectly matched CB’P (PM) and mismatched CBN’P (MM), were tested in the experiment. (b) Bar graphs showing the fluorescent intensities from the hybridization patches in (a). The error bars represent the standard deviations of the hybridization signals of nine patches. The connected line shows the discrimination ratio between the PM and MM species. In these discrimination experiments, 1.0-μL PCR products (1.6-ng CB’P or CBN’P) were applied in triplicate to the inlet reservoirs of 6 spiral channels Then the sample solutions flowed into the spiral channels by spun at 1500 rpm for 3 min first at 23 ºC (room temperature). After this operation, the channels were dried out at 3600 rpm and the temperature of the assembly was raised to 42 ºC. Then another batch of sample solutions was applied to another 6 spiral channels on the same chip and the process was repeated. The procedure was repeated similarly for hybridization at 52 ºC and 62 ºC. Reprinted with permission from [134], Copyright © 2010 Elsevier Ltd. ................................ 127
Figure 7-1 (a) The photograph of the equiforce spiral channel assembly before spinning. One inlet reservoir was filled with colored solutions and a piece of paper printed with grey position lines was placed underneath to facilitate the measurement of the liquid front position. (b) Magnified picture in (a) shows the image of inlet reservoirs and a microchannel partially-filled with red dye solution. Reproduced from [286] by permission of The Royal Society of Chemistry. ........................................... 134
Figure 7-2 (a) The layout of the equiforce spiral channel and the orthogonal curvilinear coordinate system used for the mathematical modeling of the liquid flow inside the spiral microchannel. (b) 3-D magnified view of the spiral microchannel in the curvilinear coordinate system. H and W are channel height and width, respectively. Reproduced from [286] by permission of The Royal Society of Chemistry. ........................................... 137
Figure 7-3 (a) A bird’s-eye view of the 3D geometry of the equiforce spiral microchannel used in CFD simulations. (b) Magnified view of the inlet region with a tilted inlet reservoir and a neck channel. Point A denotes the starting position of the spiral channel where the neck channel connects. (c) Magnified view shows the structured grid of the microchannel near point A. The cell widths range from 15 µm to 75 µm. The grid lines are as close to 90° as possible and small cell aspect ratios were employed to ensure a good modeling quality. Reproduced from [286] by permission of The Royal Society of Chemistry. ...................... 140
Figure 7-4 Liquid movement inside microchannels. (a), (b) and (c) show the 3 snapshot images of the disk spun at 1500 rpm, where 1 and 2 designate the 10th and 20th position lines, respectively. The black arrows denote the inlet reservoirs and the white arrows indicate the liquid front. The spiral trace extended as time increased, indicating the movement of the liquid front along the microchannels. (d), (e) and (f)
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represent the displacement-to-time plots showing the movement of both the liquid front and liquid rear meniscus in 3 adjacent spiral channels. The start lengths of the liquid front measurement are 7.8 mm, 9.3 mm, and 12.6 mm, respectively. Reproduced from [286] by permission of The Royal Society of Chemistry. ........................................... 143
Figure 7-5 (a) Liquid front displacement versus time at different rotation speeds. Data points represent experimental data and the solid lines are theoretical curves plotted using the mathematical model (The curves and data points were displaced horizontally for clarity). (b) Microscope images of 3 channels in a PDMS chip showing the width variation. The scale bar represents 100 μm. (c) Calculated variation of flow velocity as affected by the variations in channel width and depth using the proposed mathematical model. (d) Liquid front displacement versus time graph from two spiral-microchannel chips of different channel geometries. Data points represent experimental data and the solid lines are from the model prediction. Here, W, H, and U are channel width, channel height, and measured liquid-front velocity, respectively. Both microchips were rotated at 1500rpm. Reproduced from [286] by permission of The Royal Society of Chemistry. ........................................... 145
Figure 7-6 (a) Image showing the initial conditions used for transient flow simulation. The blue color represents the part of the channel filled with air and the pink color denotes liquid solutions. (b) Simulated liquid front displacement versus time at 1500 rpm with different start lengths. (c) comparison of the liquid front velocities at 1500 rpm with experimental data, mathematical modeling, simulation of transient filling flow and simulation of steady flow. Reproduced from [286] by permission of The Royal Society of Chemistry. ........................................................................ 148
Figure 7-7 (a) Liquid front displacement versus time from experimental data at 2400 rpm. The inset shows the liquid front velocities from fitting the experimental data in both cases. Because a longer acceleration time was required to achieve a higher rotation speed, the start length is much longer, which is around 50 mm. (b) Simulated results of the liquid front velocities at 2400 rpm from anti-clockwise and clockwise directions. Reproduced from [286] by permission of The Royal Society of Chemistry. ............................................................................................... 150
Figure 7-8 (a) Comparison of the centrifugal force (Fω, shown as a gray plane.) and the surface tension force (Fs, shown as a color surface) along the microchannel at 1500 rpm (b) Simulated the liquid front velocities at 1500 rpm from two solutions (A and B) with different contact angles on the solid substrate (c) Measured dynamic contact angle change of the two solutions from experimental observations. Reproduced from [286] by permission of The Royal Society of Chemistry........................................ 153
Figure 7-9 (a) Liquid front moving velocity under different rotation speeds. Both data from experimental data and from mathematical model prediction are shown. The error bars are from the measurement of 3 adjacent channels. (b) Pressure at the beginning of the spiral channels generated from the short liquid column in the neck section under
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different rotation speeds. Reproduced from [286] by permission of The Royal Society of Chemistry. ........................................................................ 154
Figure 7-10 Section of the spiral curve and the infinitesimal segment used for the calculation. Here the black solid curve is the spiral curve and the blue dashed lines are radial lines from the disk center. r and θ are the usual polar coordinates. Reproduced from [286] by permission of The Royal Society of Chemistry. .................................................................................. 157
Figure 7-11 Comparison of the simulation results using two meshes with different resolutions. (a) low-density mesh, cross-channel resolution is same as that used in the manuscript (5 × 2 cells). (b) high-density mode, the cross-channel resolution of the computational grid is 20×12 cells. (i) computational grids showing the cross-section of the microchannel. (ii) the color map of the down-channel flow velocities (us) at the cross-section of the microchannel.(iii) the color map of the transversal flow velocities (un) at the cross-section of the microchannel. The center black lines in high-resolution grid results are the symmetry plane. .............. 166
Figure 7-12 (a) Schematic diagram showing the position of the cross-section part of the microchannels used for secondary flow analysis. (b) The flow vector map combining un and uz. (c) The color map of us on the cross section. (d) The color map of un on the cross section. (e) The color map of uz on the cross section. The center black lines in (b) to (e) are the symmetry plane used during simulation. ................................................ 167
Figure 8-1 (a) The configuration of a PDMS plate with a rectangular microchannel filled with solutions. The bottom wall of the microchannel is immobilized with 3 probe strips. (b) The schematic diagram showing the simplified 2-D geometry of the above microchannel used for later numerical simulation. The two diagrams are not drawn to scale. ................. 173
Figure 8-2 (a) Schematic representation of proposed heterogeneous DNA hybridization model. The probe DNA molecules are shown as blue wave-like ribbons in the center region of the glass substrate. The target DNA molecule is a red twisted ribbon with a red pellet at one end which represents the fluorescence label. The hybridized DNA are shown as duplexes in the probe region. (b) The three kinetic processes used in the later model construction regarding the heterogeneous hybridization of target DNA: k3 and k-3 represent bulk-to-surface hybridization and dessociation of targets to the bulk phase; k2 and k-2 represent surface-to-surface hybridization and dissociation of the nonspecifically adsorbed targets; and ka and kd represent the reversible nonspecific adsorption and desorption of the targets to the surface. ....................................................................................................... 175
Figure 8-3 An example of meshed 2-D geometry of the microchannel. The grid closed to bottom wall was meshed with much higher density because it is close to the reactive surface with probe spots.......................................... 184
Figure 8-4 (a) Concentration profile of static hybridization. (b) Concentration profile of microflow hybridization. The average flow velocity is 1 mm/s and the flow direction is shown as a blue arrow. In both (a) and (b), an array of 3 probe spots has been incorporated in the model. The probe
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region width and spacing are at 200 µm. The sample concentrations at inlets are set to 10 nM and the hybridization time is 3 min.The bottom rainbow bars denote the bulk concentration scale. (c) Kinetic curves showing the change of the hybridization fraction vs. time during the static or microflow hybridization in 15 min. .................................................. 190
Figure 8-5 (a) The image of hybridization patches by flowing through 1-µL oligonucleotide samples at different concentrations in 12 min. The hybridization patches from two vertical repeated probe lines are shown. (b) The normalized hybridization signal intensities from the experimental results in (a). The error bars come from the standard deviation of 5 hybridization patches. The simulated hybridization signals are also shown for comparison. ....................................................... 192
Figure 8-6 (a) The fluorescent image of microchannel hybridization results at different flow rates. Six flow rates, from left to right, 2.0, 1.0, 0.5, 0.3, 0.2, and 0.1 µL/min have been applied. The hybridization image in the right most is from 30-min stop-flow hybridization. 1 µL of 10-nM oligonucleotide samples were applied to each microchannel. (b) The relative hybridization intensities from the left image. The error bars are from the standard deviation of 5 hybridization patches. ............................... 194
Figure 8-7 (a) The simulated results of the relative bulk target concentrations adjacent to the probe regions. (b) The simulated hybridization kinetics at different flow conditions. The hybridization time for the stop-flow method is 30-min. In the dynamic flow method, four flow speeds, from left to right, 0.01 to 1 mm/s have been simulated and the corresponding Pe values are from 10 to 10000. 1 µL of 10-nM oligonucleotide samples were applied to each microchannel. ..................... 196
Figure 8-8 (a) The simulated hybridization intensities in microchannels of 2 different depths. Here, 2 types of microchannels, 75 µm and 24 µm, are simulated and the hybridization time is 3 min in all cases. The Pe number of both types of microchannels is 1000. In stop-flow method, the hybridization time is set to 30 min. (b) Experimental results from flow hybridization of 1-µL samples in the 2 types of microchannels. ............ 197
Figure 8-9 (a) The experimental and simulation results of the effect of probe coverage on hybridization signals. Top curve with triangle labels shows the simulated hybridization signals at different probe coverage; Bottom curve with square labels shows the experimental hybridization signals at different probe coverage. (b) The simulated kinetic curves of hybridization at different probe densities. .................................................... 201
Figure 8-10 Sequence structures showing (a) a perfect-matched duplex (B-B’) and (b) a one-base-pair-mismatched duplex (B-NB’) from two 21-mer oligonucleotides. ......................................................................................... 203
Figure 8-11 The experimental hybridization results from the microfluidic hybridization of 6 groups of DNA. Each group represents two targets with one-base difference at the sequence center and the probe molecules are complementary to one of them. The 12 DNA solutions were hybridized in separated microchannels but under the same conditions at ~50°C and in 2.5x SSC for 3 min. ........................................... 205
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Figure 8-12 The simulated effect of the 2 Damköhler numbers (Da3 and Dn) on relative hybridization fraction after (a) 3-min, (b) 15-min, and (c) 60-min microfluidic hybridization. The corresponding dimensionless dissociation equilibrium constants (K3') are also shown as dashed lines in the 3 graphs. The colorscale bar beside each graph denotes the level of the relative hybridization fraction. .................................................... 207
Figure 8-13 The kinetic curves of the microchannel washing procedure at different dissociation constants. In all the cases the Da values were set to 1, which is a typical value for 20-mer duplex formation. ........................... 210
Figure 8-14 (a) Top: The fluorescence image of the hybridization results from pin-spotted DNA microarray. Bottom: The fluorescence intensity along the yellow dashed line in the top image. (b) Top: The fluorescence image of the stop-flow hybridization results from channel-spotted DNA microarray. Here, the sample channel was in horizontal and crossed two vertical probe lines. Bottom: The fluorescence intensity along the yellow dashed line in the top image. ............................................................ 211
Figure 8-15 (a) The simulated relative bulk concentration profile of target DNA at the bottom wall with a probe spot. Here, both static and dynamic hybridizations are simulated. For the latter method, 5 different flow rates were tested resulted in 5 Pe/Da ratios. (b) The simulated hybridization fraction profiles at the bottom wall with different hybridization methods. In all cases, the hybridization time is set to 3 min. ............................................................................................................. 215
Figure 8-16 The simulated hybridization fractions along the bottom wall with a probe region. The width of the probe region varies from 50 µm to 1mm. (a) Static hybridization. The insets show the experimental results from the hybridization of oligonucleotide samples with complementary probe lines with a width of 50 µm. The concentration of the oligonucleotide samples is 100, 10, and 1 nM, respectively, from left to right. (b) Dynamic hybridization. ................................................................................ 216
Figure 8-17 Simulated graphs showing the evolvement of bulk concentration profiles with a group of 3 probe spots. (a) After 1-min static hybridization. (b) After 15-min hybridization. (c) Simulation results showing the evolvement of the discrepancy of hybridization fractions on the 3 probe spots at different time. ......................................................... 218
Figure 8-18 The experimental results from the microfluidic hybridization of oligonucleotide samples at 4 concentrations. (a) Samples are prepared with 1x SSC. (b) Samples are prepared with 4xSSC. 0.1-nM targets were not detected in (a). The bottom numbers represent the probe row number. (c) and (d) show the simulated profile of bulk concentration during hybridization in 4x SSC and 1x SSC buffer, respectively. ................. 220
Figure 10-1 The 2-D geometry used in the COMSOL simulation. ................................ 233
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LIST OF TABLES
Table 1-1 Microfluidic DNA microarray hybridization conducted using the pressure-driven flow method. ........................................................................ 21
Table 1-2 Microfluidic DNA microarray hybridization conducted using centrifugal pumping. ....................................................................................................... 34
Table 3-1 Oligonucleotides and PCR products used in this study .................................. 65
Table 6-1 Oligonucleotide primers used in this study ................................................... 114
Table 7-1 Comparison of the simulation results from two different mesh densities. ..... 165
Table 8-1 The calculated free energies of 6 groups of DNA duplexes. ........................ 204
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LIST OF ABBREVIATIONS
2-D Two-dimensional
3-D Three-dimensional
AB 21-mer oligonucleotide probe designed for the detection of Botrytis cinerea. The 5’-end of the sequence is labelled by an amine group linked with a –(CH2)6– spacer
ALB 21-mer oligonucleotide probe designed for the detection of Botrytis cinerea. The 5’-end of the sequence is labelled by an amine group linked with a longer –(CH2)12– spacer
AD 22-mer oligonucleotide probe designed for the detection of Didymella bryoniae. The 5’-end of the sequence is labelled by an amine group linked with a –(CH2)6– spacer
ADF 22-mer oligonucleotide probe designed for the detection of Didymella bryoniae. The 5’-end of the sequence is labelled by an amine group linked with a –(CH2)6– spacer. The 3’-end of the sequence is labelled by a fluorescein molecule
APTES 3-Aminopropyltriethoxysilane
APTMS 3-Aminopropyltrimethoxysilane
bp Base pair(s)
cDNA Complementary DNA synthesized from a messenger RNA template
CB’ 21-mer oligonucleotides complementary to the sequence of probe AB, the 5’-end of the molecule is labelled with Cy5 dye
CB’50 Cy5 dye labelled 50-mer oligonucleotides. The central 21 bases are complementary to the sequence of probe AB
CB’P Cy5 dye labelled 264-bp PCR products amplified from genomic DNA of Botrytis cinerea
CBN’P Fluorescein labelled 264-bp PCR products amplified from genomic DNA of Botrytis squamosa, there is one base-pair difference in the
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center from the sequence of CB'P
CCD Charge-coupled device
CD Compact disk
CD’ 21-mer oligonucleotides complementary to the sequence of probe AD, the 5’-end of the molecule is labelled with Cy5 dye
CD’50 Cy5 dye labelled 50-mer oligonucleotides. The central 22 bases are complementary to the sequence of probe AD
CD’P Cy5 dye labelled 259-bp PCR products amplified from genomic DNA of Didymella bryoniae
CE Capillary electrophoresis
CFD Computational fluid dynamics
Cy5 A fluorescent cyanine dye. The number of methine groups in its polymethine chain is 5
Da Damköhler number
DMSO Dimethyl sulfoxide
DNA Deoxyribonucleic acid
dsDNA Double-stranded DNA
EOF Electroosmotic flow
FB' Fluorescein labelled 21-mer oligonucleotides complementary to the sequence of probe AB
FD' Fluorescein labelled 22-mer oligonucleotides complementary to the sequence of probe AD
FB'P Fluorescein labelled 264-bp PCR products amplified from genomic DNA of Botrytis cinerea
FBN'P Fluorescein labelled 264-bp PCR products amplified from genomic DNA of Botrytis squamosa, there is one base-pair difference in the center from the sequence of FB'P
FD'P Fluorescein labelled 259-bp PCR products amplified from genomic DNA of Didymella bryoniae
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GNP Gold nanoparticle
MEMS Microelectromechanical systems
MM Mismatch
MMA Microfluidic microarray assembly
ODE Ordinary differential equation
Oligo(s) Oligonucleotide(s)
PBS Phosphate Buffered Saline
PCR Polymerase chain reaction
PDE Partial Differential Equation
PDMS Polydimethylsiloxane
Pe Péclet number
PM Perfect match
PMT Photomultiplier tube
Re Reynolds number
RNA Ribonucleic acid
rpm Revolutions per minute
SDS Sodium dodecyl sulphate
SNP Single-nucleotide polymorphism
SSC Sodium chloride-sodium citrate buffer
ssDNA Single-stranded DNA
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LIST OF SYMBOLS
C Bulk-phase concentration of targets.
C0 Initial bulk-phase concentration of targets.
Cw Bulk-phase concentration of targets at bottom wall.
CDX Bulk-phase concentration of the duplex part in PCR product samples.
CLC Bulk-phase concentration of the loose-coiled target strands in PCR product samples.
CSC Bulk-phase concentration of the super-coiled target strands in PCR product samples.
dH Hydraulic diameter of the microchannel.
Ds Two-dimensional (i.e., surface phase) diffusion coefficient.
D Three-dimensional (i.e., bulk phase) diffusion coefficient.
Da1 Damköhler number of the target adsorption process.
Da2 Damköhler number of the surface-to-surface hybridization process.
Da3 Damköhler number of the bulk-to-surface hybridization process.
Dn Damköhler number of the dissociation process of the hybridized duplexes on the surface.
en Unit vector in n direction of the proposed orthogonal curvilinear coordinate system.
es Unit vector in s direction of the proposed orthogonal curvilinear coordinate system.
er Unit vector of radial distance in the cylindrical coordinate system.
eθ Unit vector of azimuth in the cylindrical coordinate system.
f Volume fraction of fluid in partially filled grids during the CFD simulation.
Fs Centrifugal force.
Fω Surface tension force.
g Gravitational constant.
h Scale factor of the proposed orthogonal curvilinear coordinate system in the s direction.
H Height of the microchannel.
J Mole flux of target DNA molecules in bulk solution.
k Degree of spirality of the spiral microchannel.
xxxii
k Unit vector in z direction of the proposed orthogonal curvilinear coordinate system.
kn Empirical nucleation constant.
ka Kinetic association constant for nonspecific adsorption of target strands.
kd Kinetic dissociation constant for nonspecific adsorption of target strands.
k2 Kinetic association constant for surface-to-surface hybridization.
k-2 Kinetic dissociation constant for surface-to-surface hybridization.
k3 Kinetic association constant for bulk-to-surface hybridization.
k-3 Kinetic dissociation constant for bulk-to-surface hybridization.
kdx Kinetic association constant for bulk-phase renaturation of PCR products.
k-dx Kinetic dissociation constant for bulk-phase renaturation of PCR products.
ksc Kinetic association constant for bulk-phase formation of the secondary structures of PCR products.
k-sc Kinetic association constant for bulk-phase formation of the secondary structures of PCR products.
KD' Dimensionless dissociation equilibrium constant for nonspecific adsorption of targets.
K2' Dimensionless dissociation equilibrium constant for surface-to-surface hybridization of targets.
K3' Dimensionless dissociation equilibrium constant for bulk-to-surface hybridization of targets.
KDX Dissociation equilibrium constant for bulk-phase PCR products.
KSC Dissociation equilibrium constant for the super-coiled part in PCR products.
l Liquid front displacement along the microchannel.
L Length of the microchannel.
n Across-channel distance in the proposed orthogonal curvilinear coordinate system.
NA Avogadro’s number.
Pe Péclet number of the microflow.
p Fluid pressure.
P0 Fluid pressure at the inlet of the spiral channel.
Pm Fluid pressure at the meniscus of liquid front.
Ps Fluid pressure from the surface tension of meniscus of liquid front.
r Radial distance from the rotation center to the liquid front.
r0 Initial radial distance from the rotation center to the start of the spiral channel.
r Average radial distance from the rotation center to the liquid column.
Δr The radial extent of the liquid column subject to centrifugal force.
xxxiii
R Position vector to a point described by (n, s, z) system within the microchannel.
Re Reynolds number of the microflow.
Rp Radius of each probe molecule occupied on the glass surface.
Rt Gyration radius of a DNA molecule in solution.
Rads Adsorption rate of DNA targets.
Rbhy Reaction rate of bulk-to-surface hybridization.
Rshy Reaction rate of surface-to-surface hybridization.
s Distance along the spiral channel in the proposed orthogonal curvilinear coordinate system.
t Time.
u Flow velocity in x direction (along the channel).
u Vector field of fluid velocity.
U Characteristic flow speed, measured as the average liquid front speed from the experiment.
us Fluid speed in the n-direction of the proposed orthogonal curvilinear coordinate system.
un Fluid speed in the s-direction of the proposed orthogonal curvilinear coordinate system.
uz Fluid speed in the z-direction of the proposed orthogonal curvilinear coordinate system.
W Width of the microchannel.
z Distance perpendicular to the spiral channel in the proposed orthogonal curvilinear coordinate system.
α Angle between the radial direction and the tangent of the spiral channel.
α0 Initial angle between the radial direction and the tangent of the spiral channel at the start position.
γ Surface tension coefficient of the liquid.
Δ Laplacian operator.
ΔT A customized operator similar to the Laplacian operator.
ΔG Free energy of duplex formation.
ΔΔG Free energy difference between MM duplex formation and PM duplex formation.
ε1 Ratio of bulk-phase targets to maximum adsorbable targets.
ε2 Ratio of surface adsorption capacity relative to hybridization capacity.
ε3 Ratio of bulk-phase target numbers to maximum hybridizable target numbers.
φ Ratio between the surface diffusion coefficient (Ds) and the bulk diffusion coefficient (D).
xxxiv
η Surface concentration of non-specifically adsorbed target DNA molecules.
ηmax Maximal number of the non-specifically adsorbed target DNA at a unit area of the glass surface.
θ Contact angle of the fluid on either PDMS or glass surface.
Θ Surface concentration of the hybridized duplexes.
Θ0 Probe density, equal to the maximal surface concentration of hybridized duplexes.
κ Curvature of the spiral microchannel.
ξ Strand complexity in nucleotide numbers (nt).
Γ Strand length in nucleotide numbers (nt).
σ3 Persistence length of the target DNA in bulk solution.
µ Dynamic viscosity of the fluid.
ν Kinematic viscosity of the fluid.
ω Angular speed.
Ω Angular velocity field.
ρ Fluid density.
χ3 Reaction success probability.
1
1: INTRODUCTION
1.1 Fundamentals of DNA microarray hybridization
1.1.1 The building blocks of DNA
Deoxyribonucleic acid (DNA), which is found primarily in the nucleus of a
cell, serves as the repository of genetic information. DNA is a linear polymer built
from different monomeric units called nucleotides. A nucleotide consists of three
chemical units including a nitrogenous base, a pentose sugar (2-deoxyribose),
and a phosphate group. The nitrogenous bases in DNA include two purines,
adenine (A) and guanine (G), and two pyrimidines, thymine (T) and cytosine (C).
The structures of the nucleotides and the four nitrogenous bases are listed in
Figure 1-1.
Figure 1-1 (a) General structure of the nucleotide. The nitrogenous base and the pentose sugar are linked each other through N-glycosidic linkage. The official numbering system is also shown. (b) The two purine nitrogenous bases in DNA. (c) The two pyrimidine nitrogenous bases in DNA.
(c) (b)
Pyrimidine Purine
O
HOH
HH
HH
OP-O
O-
OBase
1'
2'3'
4'
5'
(a)
N
NH
NH2
O
HN
NH
O
O
N
N NH
N
NH2
HN
N NH
N
O
H2N
Adenine Guanine Thymine Cytosine
2
1.1.2 DNA duplex structure
In its natural state, DNA is a double helix consisting of two polynucleotide
strands, as discovered by James Watson and Francis Crick in 1953 [1]. The two
strands wrap around each other in a helical "twisted ladder" structure, or double
helix, as shown in Figure 1-2(a). The covalent sugar-phosphate backbone is on
the outside of the double helix with alternating deoxyribose and phosphate
groups, and the nitrogenous bases are located in the centre (Figure 1-2(b)).
Figure 1-2 (a) Watson-Crick model of a 21-bp DNA double-helix. The pentose-phosphate backbones of the two strands (shown in blue and red ribbons) form a right-handed double helix. The DNA structure was generated with the DNA modeling server by Vlahovicek et al. [2]. Image visualization was performed with the Chimera molecular modeling system [3]. (b) Chemical structure of the specific hydrogen bonding in a DNA duplex. The duplex is stabilized by hydrogen bonding between complementary base pairs and (though not obvious from this drawing) by base stacking interactions between adjacent base pairs.
(b) (a)
N
NN
N
HN
O
O
P O
O
O
-ON
HN
ONO
O
P O
O
-O N
N
NO
NH
NO
O
P O
O
-ON
O
O
H3C
NO
OH
P O
OH-O
H
H
H
H
H
N N
N
NHN
O
O
PO
O
O
O-
N
HN
O
NO
O
PO
O
O-
N N
NO
NH
N
O
O
PO
O
O-
N
O
O
H3C
N
O
OH
PO
OH
O-
H
H
H
H
H
A
C
T
G
A
T
C
G
5’-end
5’-end
3’-end
3’-end
3
The most remarkable feature of the Watson-Crick structure is that the two
DNA strands are held together by the formation of specific hydrogen bonds
between nitrogenous bases. There are only two types of base pairings found in
the DNA duplex: A·T and G·C. The geometries of these complementary A·T and
G·C base pairs, the so-called Watson-Crick base pairs, are shown in Figure
1-2(b). The double helix structure is also stabilized by interactions between the
flat aromatic rings of adjacent base pairs [4]. Other combinations of bases (e.g.
A·G or T·T) destabilize the double helix structure [5].
1.1.3 DNA hybridization analysis
The formation of DNA duplexes from two complementary polynucleotide
strands is called hybridization or annealing. As depicted in Figure 1-3, the 2-step
process starts with the intermolecular collision between two strands to form an
intermediate state, in which a few base pairs have formed (also known as
nucleation). This is followed by the second step that the rest of the
complementary sequences join together much like a zipper closing [6, 7].
Because the second step is rapid and is in the order of 106-107 base pairs per
second, the first step of intermediate formation is the rate-limiting step during
hybridization [8, 9].
4
Figure 1-3 Schematic view of the DNA hybridization process. (a) Two complementary single-stranded DNA before hybridization. (b) Intermediate state with a few base pairs from strand collision. (c) Hybridized DNA duplex from zippering step.
The kinetics of DNA hybridization is dependent on the properties of the
DNA sequences and various experimental factors. In the former case, the
hybridization rate constants of DNA (in aqueous solutions) are inversely
proportional to the number of nucleotides of non-repeating sequences for the
given DNA [10]. Therefore, the hybridization rate of two shorter complementary
oligonucleotides is usually much faster than the hybridization of longer DNA
strands. In terms of experimental factors, the DNA hybridization rate is affected
by temperature, viscosity, and ionic strength. First, the apparent rate constant
shows a “bell-shaped” dependence on temperature, with a broad flat maximum at
temperatures that are from 15 to 30°C below the melting temperature [10, 11].
Second, because the DNA molecules are brought together by diffusion before the
intermediate formation [7], the hybridization rate decreases in viscous solutions
[10]. Third, DNA-DNA hybridization is also highly dependent on the ionic strength
of bulk solutions. The two negatively charged DNA strands strongly repel each
other at low salt (in NaCl) concentrations, and adding salt shields this repulsion
Zippering
Fast
Nucleation
Slow
(a) (b) (c)
5
[11]. At a constant temperature, the hybridization rate is proportional to the cube
of [Na+] in low-salt concentration (< 0.2 M), although this strong dependency
diminishes at higher [Na+] [12-14]. Moreover, it should be noted that during the
heterogeneous hybridization between solution-phase DNA and surface-
immobilized DNA, the hybridization rate can be slower due to the additional steric
effect involved in the surface reaction [15, 16].
DNA hybridization is a reversible process. For example, when the duplex
DNA solution is heated above a characteristic temperature, the double-helix
structure collapses and the two complementary strands dissociate into two
flexible single-stranded DNA. This duplex dissociation process is also known as
denaturation or melting. The characteristic temperature is named as the melting
temperature (Tm). Depending on the sequence properties (described as chain
length, GC content, and mismatch percentage) and the solution conditions (pH
and ionic strength), the double-stranded DNA can have a very distinct Tm value,
as reported elsewhere [17, 18]. Tm is thus an important thermodynamic
parameter in devising DNA hybridization assays, such as probe/primer design,
the selection of temperature in hybridization and washing steps, as well as the
development of methodology to identify DNA with single base-pair mismatch [19-
21].
Because of the high-strength, sequence-specific base pairing between
complementary DNA strands during hybridization, DNA molecules themselves
are the perfect set of agents to identify particular DNA sequences. Therefore, the
principle of DNA hybridization analysis is to use a known, well-characterized
6
population of DNA molecules (i.e. probes) to search for complementary
sequences within an unknown population of DNA samples of biological or
medical interest (i.e. targets). Here, probes are short single-stranded DNA
molecules prepared either from synthetic oligonucleotides (< 100 bases) or from
DNA fragments (< 1000 bases) [19]. On the other hand, target DNA samples are
frequently made by amplifying cell-based DNA extracts using polymerase chain
reaction (PCR) technology. Because the PCR products obtained are usually
double-stranded, the DNA targets have to be denatured to the single-stranded
format by heating before being exposed to probes. With proper labels on the
probe or the target, the DNA duplexes formed during hybridization could be
identified and quantitated.
Figure 1-4(a) depicts a schematic diagram of the preparation of
probe/target DNA for the hybridization test. With the knowledge of the genomic
DNA sequence, the probe DNA sequence (short 21-base oligonucleotide) is
selected based on the design criteria of specificity, melting temperature, and
structural stability [22]. The DNA probes are then synthesized chemically and
functional groups such as labels may be added during the synthesis. The
genomic DNA extracts from cell cultures are first denatured by heat and then
amplified by PCR to make the DNA target samples (260 bp). Fluorescence labels
can be integrated into the target sequence during the DNA amplification step.
The analysis for a particular DNA sequence is based on the premise that the
probe can find its complementary target in the sample of interest through
hybridization. Either labeled targets (Figure 1-4b) or labeled probes (Figure 1-4c)
7
can be used to identify the duplex, and the former format is adopted in this thesis.
In earlier solution-phase hybridization assays, the probe-target duplexes are
separated from the reaction mixture by chromatography and are quantitated by
the labels on the duplex [23]. The modern microarray technology relies on the
solid-phase hybridization for the ease of separation and this method will be
discussed in Section 1.1.5.
Figure 1-4 (a) Preparation of DNA targets from genomic DNA. Here, the genomic DNA duplexes are denatured to two single strands. One of the strands (highlighted in yellow color) are then amplified and labeled with proper tags for later hybridization analysis. (b) and (c) show the two formats of DNA hybridization analysis: (b) Target DNA is labeled. (c) Probe DNA is labeled.
(b)
(a)
Target
Probe
Target
Probe
Genomic DNA
(c)
... ACTTTGTTGCTTTGGCGAGCTGCCTTCGGGCCTTGTATGCTCGCCAGAGAATACCAAAACTCTTTTTATTAATGTCGTCTGAGTACTATA ... ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
... TGAAACAACGAAACCGCTCGACGGAAGCCCGGAACATACGAGCGGTCTCTTATGGTTTTGAGAAAAATAATTACAGCAGACTCATGATAT ...
1) Heat denaturation 2) PCR amplification 3) Labelled with fluorescence tags at the end
... TGAAACAACGAAACCGCTCGACGGAAGCCCGGAACATACGAGCGGTCTCTTATGGTTTTGAGAAAAATAATTACAGCAGACTCATGATAT ...
Selected region for target recognition
DNA targets ready for hybridization analysis Fluorescence
labels
Synthetic oligonucleotide probes
CGCCAGAGAATACCAAAACTC
8
1.1.4 Hybridization of mismatched DNA sequences
Other than the hybridization of complementary DNA sequences in
perfectly matched (PM) situation, DNA sequences with a few mismatched (MM)
base pairs can hybridize too. For example, in Figure 1-5, the base thymine lining
up opposite to a guanine group would be a mismatch (The T·G mismatch). As
long as most of base pairs in the duplex do match and form hydrogen bonds, the
strands will hybridize, albeit giving rise to a distorted and less stable duplex.
Figure 1-5 (a) Distorted DNA duplex structure from two T·G mismatches in the center. The two green arrows indicate the two T·G mismatches. (b) The sequence of the duplex shown in (a). The blue strand is 5'-CGCATTACGC-3', and the red one is 5'-GCGTGGTGCG-3'. (PDB access number: 1SNH [24])
The study of DNA duplexes with mismatched base pairing has significant
implications. In particular, during studies of single nucleotide polymorphism
(SNP) and point mutation, there is only a single nucleotide variation at a specific
location in the genome (the variation can lead to the development of disease in
some cases) [25-28]. It is thus important to recognize and reliably discriminate
the target sequence from its peers with only single base difference.
(a) (b)
C C C A
T T
A C G C
G C G T
G G
T G C G
9
Hybridization under proper conditions (e.g. temperature) is a common
method used to achieve discrimination between the DNA sequences with single
base-pair difference [25]. The approach is based on revealing differences in the
stability of perfectly-matched (PM) and mismatched (MM) DNA duplexes,
because the presence of MM base pairs significantly reduces the overall stability
of the duplex. This can be observed through a reduction of the Tm of MM
duplexes as compared to that of PM duplexes [29, 30]. The destabilization effect,
or reduction of Tm, is determined by a number of factors including the probe
length (e.g. 20-mer or 50-mer), the mismatch type (e.g. T·G vs. T·T), etc. [14,
31]. For instance, the Tm is estimated to decrease by 1°C for every 1%
mismatch in the duplex (e.g. 1-bp mismatch in a 100-mer probe) [30]. Therefore,
the reduction of duplex Tm due to single base-pair mismatch diminishes for longer
duplexes. Hence it is necessary to use short oligonucleotide probes (typically ~20
bases) to increase the percent of mismatched region for the successful
discrimination of MM DNA targets [13].
10
Figure 1-6 Hybridization-based approaches for the discrimination of SNP sequences. (a) Targets are prepared from two SNP sequences with only one base-pair difference. (b) Fluorescence-labeled targets hybridize to probe molecules. The mismatched sequences form unstable duplexes. (c) The unstable MM duplexes are denatured and removed by high-stringency washing conditions. (d) Fluorescence signals from retained PM duplexes.
By selecting proper hybridization conditions, PM duplexes can be
distinguished from MM duplexes. In hybridization applications, the degree of
mismatching tolerated in duplex formation is called “stringency” [20]. Under
conditions of low stringency (low temperature or high salt concentration), even
mismatched strands will be able to bind and give a hybridization signal, although
it is a false positive one. Under conditions of high stringency (high temperature or
low salt concentration), only PM strands will hybridize and stay together.
Therefore, by carefully controlling test conditions to an acceptable level of
stringency, MM targets can be removed from binding to probes and only PM
targets give hybridization signals in a reproducible manner (Figure 1-6).
(b) (a)
High-stringency washing
(c)
AT
GT
AT
T
Fluorescence analysis
ATAT
GCGC
T
SNP specific probes
Two sequences with single base-pair difference
(d)
11
1.1.5 DNA microarray and its applications
DNA microarray can be defined as a miniaturized, ordered arrangement of
different probe DNA populations fixed onto a solid surface at precisely defined
positions in a grid format, enabling the analysis of numerous genes in parallel by
specific hybridization [14, 32]. The concept of DNA microarray was evolved from
the Southern blotting technology using the solid-phase hybridization method
developed in the early 1990s [33]. Compared to the solution hybridization test,
where the probe-target duplexes have to be isolated by chromatography [34],
microarray hybridization is more efficient in the removal of un-hybridized DNA
molecules and in the reduction of reagent consumption due to the miniaturized
architectures. Another significant advantage of the microarray method is that the
DNA identification processes can be completed in a parallel manner. DNA
microarrays have been widely used in many applications in molecular biology,
biochemistry, and biotechnology fields, as reviewed elsewhere [35-39].
In general, there are two formats of DNA microarray, depending on the
probe arraying technologies: in situ synthesized or spotted. The first format
involves light-directed in situ synthesis of oligonucleotide probe arrays, which is
pioneered by Affymetrix GeneChip® technology [40, 41]. The technology
features high probe density, where more than 6 million different oligonucleotide
populations can be integrated on a chip [42]. Another cheaper and more flexible
format is to spot probe DNA molecules onto a functionalized glass slide [43]. The
probe DNA molecules can be either DNA fragments with known identities [44] or
pre-synthesized oligonucleotides [45]. As shown in Figure 1-7a, a robotic arrayer
12
with multiple pins is used to simultaneously pick up and deposit DNA solutions.
The probe molecules can also be spotted by inkjet methods [46] or more
recently, by microfluidic methods. The latter approach will be further discussed in
the following sections.
When DNA microarray is used in a hybridization assay, a test sample,
which is an aqueous solution containing fluorescently labelled target DNA, is
applied to the microarray slide and allowed to hybridize to the probe molecules
(Figure 1-7c). After the slide is washed to remove nonspecific hybridization
(Figure 1-7d), it is read in a high-resolution laser scanner (Figure 1-7e). The
signal emitted from each spot is then collected to produce an image, where
differences in fluorescent labels and signal intensities result in different colors
with different brightness, respectively (Figure 1-7f). Image-processing programs
are used to find the spots and quantify them [47]. The hybridized target can also
be measured chemiluminescently, electrochemically, or radiochemically with
different labels [35, 48]. The hybridization signal intensity of a microarray spot
depends on the target abundance, but also on the particular probe-target binding
affinity.
13
Figure 1-7 Hybridization assay with spotted probe microarray. (a) Microarray probe spotting pins used in a commercial microarrayer. The photo is adapted from the product datasheet of SpotBot® Titan High-Capacity microarrayer. (b) Glass slide with chemically-modified surface ready for probe binding. The slide can be labeled with barcode for easy identification. (b) Microspotting probe molecules on the slide. The lower image shows surface tethered probe sequences. The individual probe sequences can be identified by the position of the corresponding feature on the regular microarray grid. (c) Hybridization. Target solutions are applied to the slide and are incubated in a heated humidified box. Labeled targets can freely diffuse over the microarray surface until they hybridize with a complementary probe (lower image). (d) Washing step. After hybridization, unbound targets are washed away with buffer solutions as shown in the lower image. (e) Microarray image analysis. Quantification of the surface bound targets is performed by measuring the fluorescence intensity of the hybridization spots using a fluorescence scanner.
Although the DNA microarray technology was developed only very
recently, numerous important applications have already been developed, and
their impact on biomedical research and diagnosis is dramatic. Here, tracking
gene transcripts and assaying DNA variation (genotyping) are considered as the
(b) (c) (d) (e) (f)
Scanning Washing Hybridization Spotting
(a)
14
main applications of the DNA microarray method [14, 39]. The first application is
used to compare gene expression profiles of closely related cell types, or of
identical cells that are exposed to different environments, such as the presence
of a drug [49, 50]. In terms of DNA variation assays, microarray hybridization
could help in tracking disease genes. It can also be used to identify
microorganisms, and this is important in pathogen control, safe food production,
and agricultural industry [51]. Moreover, vigorous efforts have been made to
identify and catalogue single nucleotide polymorphism (SNP) markers [20]. In this
thesis, the second application of microarray hybridization has been explored for
the identification of fungal pathogen DNA. At last, it should be noted that in
addition to transcript profiling and genotyping, microarrays can also be used in
studying protein-DNA interactions [52], DNA sequencing [53], and many other
applications [39].
1.2 Introduction to microfluidic DNA microarray technologies
With the rapid growth of microelectromechanical systems (MEMS),
microfluidic technology has developed quickly over the past two decades. By
combining the fields of microfluidics and DNA microarrays, the advantages of
both fields can be exploited simultaneously [54-56]. Since microfluidics deals with
the transfer and control of a small amount of fluids in microscale flow
configurations, one obvious advantage of using a microfluidic system is the
dramatic reduction in the sample volume. Instead of handling a volume of the
milliliter scale, a microfluidic chamber could have a volume as little as 1 picoliter
[56]. Samples such as proteins and DNA extracts from a few selected cells are
15
scarce or unavailable in large amounts; microfluidics therefore provides a way to
analyze these materials efficiently. The small volumes of the microfluidic systems
also make it possible to develop compact and portable lab-on-a-chip devices that
can be manufactured at low cost by mass production.
The second advantage of using microfluidic technology is that the
microarray hybridization kinetics of target nucleic acid can be accelerated. In
conventional DNA microarray hybridization, samples, which are typically >30μL,
are incubated for ~12h with the probe microarrays on a glass slide by covering
the solution with a thin coverslip [19]. At first, this static hybridization is
characterized by a reaction-limited process. After an initial time period, target
depletion renders the hybridization process diffusion-limited [57, 58]. Because
diffusion coefficients (D) for DNA (21–6000 bp) in aqueous solutions are on the
order of 10-7 cm2·s-1 [59], the average travel distance ( L Dt= ) of the target
nucleic acid solely due to diffusion in 24 h is ~1 mm. Considering that the
horizontal length scale of a microarray is on the order of a few centimeters,
hemispherical depletion volumes form around each probe [60]. Pappaert et al.
found that for an analysis time of 24 h the maximum binding efficiency was less
than 0.2 %, and a six-day analysis would be required for an efficiency of 2% [61].
On the other hand, recent microfluidic technology is characterized by the
advantage of the reduction of the diffusion distance. Moreover, liquid movement
in microchannels enhances the mass transport of target molecules and
accelerates the hybridization of target molecules with probes on the substrate
surface.
16
Microfluidics also offers the advantage of multi-sample capabilities on one
single chip. Conventional microarray experiments usually employ one sample on
one glass slide [19]. However, in the applications of genetic mutation analysis,
clinical diagnostics or microorganism identifications, direct comparison between
different samples on the same chip would be preferable because the quality of
slides with probe arrays varies from batch to batch [36]. Microfluidics allows for
the delivery of controlled volumes of samples and reagents to the DNA
microarray. By integrating multiple channels onto one chip, high-throughput
multisample analysis has been achieved [62-65].
In the development of microarray hybridization assays, many different
parameters such as temperature, ionic strength, and washing buffer conditions,
need to be optimized. The microfluidic method has the capability of handling
multiple samples (e.g. with different concentrations or different ionic strengths) as
well as accurate control in liquid flow and temperature, and such a method has
been developed for automated selection of optimal assay parameters [66].
Applications involving the combination of microfluidic technology with DNA
microarray hybridization are listed in Table 1-1. The table summarizes the
sample properties (sample types, sample number, sample volume and
concentrations), chip properties (chip materials and chip bonding methods), and
flow and hybridization conditions of various experiments.
1.2.1 DNA hybridization in microfluidic chambers
In conventional microarray hybridization protocols, DNA sample solutions
are loaded directly onto the glass slide surface and are incubated for hours. To
17
overcome the problem of the diffusion barrier during DNA hybridization, several
methods have been employed. For instance, some early improvements utilized
electric fields to concentrate the negatively charged molecules at probe zones.
By integrating microelectrodes onto the microarray substrate, negatively charged
DNA molecules in sample solutions were electrically attracted to the probe area
(positively charged microelectrodes) and the hybridization process was thus
accelerated [67-69]. In another approach, a microfluidic chamber was used to
cover the area with spotted probes; sample DNA solutions were then delivered to
the chamber and hybridized with the probes [70]. When the microarray area was
small and the chamber covered only a small part of the glass slide, simple
pressure-driven flow could be used [71, 72] as the solution containing the target
nucleic acids was able to move throughout the chamber and encounter every
single probe. When the microarray area is larger, however, the total sample
volume was increased and the efficiency of the hybridization was reduced. In
order to solve this problem, several approaches have been developed to improve
the efficiency of the chamber hybridization process and reduce the total sample
volume. For example, Lee et al. proposed a recirculating microfluidic device for
the hybridization of oligonucleotides to DNA microarrays [73]. The probe array
has 676 features and its total area is 62.4 mm2. The circulatory flow was
generated through a peristaltic pump connected to both ends of the
microchamber (Figure 1-8a). For the results from complementary DNA targets
shown in Figure 1-8b, the sample volume was 100 µL and hybridization time was
completed at 2 h, as compared to 16 h in the conventional static method [19].
18
Quake and co-workers constructed a more complicated PDMS device for larger
hybridization chambers (270 mm2) [74]. As shown in Figure 1-8c, the bifurcating
channel design equalized the liquid flowing into the chambers and the
herringbone indentations in the bridge channel promoted dynamic mixing.
Signals from their microfluidic hybridization method are over 3-4 fold higher than
those of the static hybridization method (Figure 1-8d).
Figure 1-8 (a) Diagram for sample recirculation system on the hybridization chamber. (b) Hybridization image of fluorescence-labelled target nucleotide with 0.1 mL·min-1 continuous recirculating flow on a DNA microarray for 40 min. Reproduced from [73] by permission of The Royal Society of Chemistry. (c) Chaotic mixing of the dye solutions in two PDMS microfluidic chambers facilitated by the herringbone indentations in the bridge channel. (d) Signal improvement by microfluidic mixing on a home-spotted microarray. Top: Dynamic; Bottom: static hybridization. Reprinted with permission from [74], Copyright © 2006 John Wiley & Sons, Inc.
(b) (a)
(d) (c)
19
For a microfluidic chamber with a size comparable to a standard
microscope slide, liquid profiles have to be carefully designed to achieve an
equally distributed coverage of sample solutions over the microarray area as well
as minimizing the amount of air trapped during filling. Different methods have
been developed to induce convective microflows inside chambers. Adey et al.
integrated two air-driven chambers on the chip and the pneumatic system
created a convective flow of hybridization fluid across the microarray slide [75].
Similar reciprocal flow was achieved by employing a mechanical rotator [60]. In
addition to these methods, shear-driven microflows from moving the coverslip
back and forth or circularly were also explored [61, 76, 77]. Moreover, Yuen et al.
proposed a closed-loop microfluidic device consisting of two interconnected
reaction chambers. Circulatory microflows in chambers were generated by the
rotation of the magnetic stirring bars in the end reservoirs [78]. Liu et al.
introduced a method called cavitation microstreaming (Figure 1-9), where
acoustic microflows accelerated chamber hybridization by up to 5 fold in reaction
kinetics [79]. Other groups have proposed designs to increase hybridization
efficiency in large chambers [80-82]. For example, McQuain et al. reported a
coordinated pump and valve system to construct a chaotic mixer to enhance
microarray hybridization, as shown in Figure 1-10. It was reported that the
number of targets hybridized in dynamic hybridization was ~3-fold more than that
in the static hybridization, and the reaction time was shortened from 24 h (static)
to 4 h (dynamic) [80].
20
Figure 1-9 (a) Schematic showing a number of air bubbles in the top layer of the DNA biochip chamber. An energetic cavitation streaming motion created by the PZT transducer was observed in the vicinity of each bubble. (b) Top image: fluorescence image of a biochip after 2-h static hybridization; Bottom image: fluorescence image of a biochip after 2-h hybridization aided with cavitation microstreaming. Reprinted with permission from [79], Copyright © 2003 American Chemical Society.
Figure 1-10 (a) Illustration of the coordinated pump and valve used for dynamic hybridization. Fluids are extracted and reinjected to the hybridization chamber under a protocol to induce chaotic movement inside the chamber. (b) Photographs of dye solution mixing in the hybridization chamber after 2 cycles of liquid removal and reinjection processes using a 30-µL stroke volume. The dye distribution appears to be homogeneous after 16 cycles. Reprinted with permission from [80], Copyright © 2004 Elsevier Ltd.
(b) (a)
(b) (a)
21
Table 1-1 Microfluidic DNA microarray hybridization conducted using the pressure-driven flow method.
Ref. Number of probe features
Sample volume
(μL)
Sample concentration
Sample type Number
of samples
Hybridization time and
temperature
Chip materials*
Substrate materials
Chip bonding* Flow method and applications
[71] High 95 >500 copies
in vitro transcribed 1.6
kb RNA 1 20 min at
37°C PC PC Screws and clamp
Pneumatic controlled flow, integrated sample extraction, amplification and washing facilities.
[80] 102 30-50 N/A 725bp PCR amplicons 1 10 or 60 min
at 42°C Acrylic Glass Rubber
gasket with bolts
Syringe pumping, chaotic mixing chamber design.
[76] 1760 5 8µM cDNA 1 60 min at 42°C
borosilicate glass Glass Clamp Shear driven by a rotating chamber, compared with a
diffusion-driven hybridization system.
[63] 16 10 N/A PCR amplicons 32 2 h at 50°C PMMA Glass PDMS Consists of 32 individually addressable array reaction chambers.
[77] 360 5 to 209 N/A PCR amplicons 1 30 or 60min at 42°C
borosilicate glass Glass Clamp Shear driven by a rotating chamber, found that velocity
field disturbs the binding process at the binding site.
[83] 90 200 5pM oligonucleotides 1 15 min at 50°C
PS, PC, PMMA, or
PP
PS, PC, PMMA, or
PP
Adhesive tape
Syringe pumping, oscillation flow, investigated for attaching oligonucleotide probes on four different types of plastic surfaces.
[74] 9500 70 0.8 or
1.6 ng/µL
cDNA 1 2h at 52°C PDMS glass Reversible bonding
Peristaltic pumping enhanced hybridization signal from microfluidic chaotic mixing.
[61] 216 7.5 or 20 1ng/µL cDNA fragments 1 10 to 30 min at 42°C
borosilicate glass Glass Weight Induction of a convective flow using a shear-driven
microchannel flow system.
[75] 6912 60 N/A PCR amplicons 1 Overnight at 42°C plastic Glass Laminating
adhesive Pneumatic control, integrating two air-driven bladders that continuously mix the hybridization fluid.
[79] high 45 10nM oligonucleotides or PCR amplicons up to 4 2 h at 37°C PC Glass Double-
sided tape Microflow induced from acoustic microstreaming.
[78] 96 150 0.12-6 pg/µL cDNA 1 2 h at 42°C PDMS or
plastic Glass Double-sided tape Fluid circulation inside the chamber by magnet stirring.
[72] 1000 10 10 nM oligonucleotides 1 5 h at 30°C PC PC Polyolefinic or PP foil.
Syringe pumping, online monitoring of microarray hybridization on a polymer chip.
[73] 676 400 1µM oligonucleotides 1 Various, up to 2h Glass Glass Mylar layer
(PET)
Peristaltic pumping, recirculation flows in the chamber, hybridization kinetics and the effects of chamber configuration were studied.
22
[84] low 6 50pM oligonucleotides 1 up to 6min PDMS glass Reversible bonding
Syringe pumping, characterization of DNA hybridization kinetics in a microchannel.
[85] 5 2.8nL to 460 nL
50pM to 500
pM oligonucleotides 1 20 to 120 sec PDMS glass Reversible
bonding Electrokinetic delivery of nanoliter sample volumes and rapid removal of nonspecific adsorption.
[86] 4 2 down to 10 pM
oligonucleotides or PCR amplicons 1 2 min at 50°C PMMA PMMA Heat
annealing
Syringe pumping, detected point mutations in oncogene fragments using universal zip code arrays placed into plastic microchannels.
[87] 8 N/A N/A oligonucleotides or 1.4 kb ssDNA 1 30 min PMMA glass N/A
Pneumatic control, oscillation flow, hybridization efficiency improved by introducing velocity and extensional strain rate.
[88] 9 N/A N/A oligonucleotides or 1.4 kb ssDNA 1 30 min at
42°C glass glass Clamp Pneumatic control, oscillation flow, combined with hot-region temperature and cold-region flow effects provided additional efficiency in DNA hybridization.
[89] 16 25 N/A PCR amplicons up to 4 30 min at 50°C PC PC Adhesive
tape Plastic chip, integrated air pump to allow oscillation of the hybridization mixture.
[90] 50 1 50pM-90nM oligonucleotides 1 500s at RT PMMA glass Clamp Syringe pumping, oscillation flow, discrimination of
single-base-pair-mismatch.
[91] 8 0.3 10pM oligonucleotides 8 5min at 22°C PDMS glass Reversible bonding
Vacuum suction, intersection format, proposed theoretical models to predict hybridization rates for both microfluidic and conventional microarrays.
[92] 8 0.5 0.1-2 μM oligonucleotides 8 30 min at 20-
40°C PDMS PC Reversible bonding
Intersection format, fast surface activation of plastic substrate.
[93] 16 N/A N/A oligonucleotides or PCR products 16 1h at 55°C PDMS PMMA or
PC Reversible bonding
Hydrostatic flow, intersection approach hybridization on plastic chip, parallel detection of two low-abundant DNA point mutations in the oncogenes.
[94]ǂ 16 1 1.4 ng/μL
oligonucleotides or PCR amplicons 16 5 min at 50°C PDMS glass Reversible
bonding Vacuum suction, intersection approach hybridization, discrimination of two pathogen PCR amplicons.
[95] ǂ 16 1 N/A oligonucleotides or PCR amplicons 16 RT PDMS glass Reversible
bonding
Vacuum suction, intersection approach hybridization, room temperature discrimination of two pathogen PCR amplicons.
[96] 6 1 N/A 1.7kb RNA N/A 1 h at 27°C PDMS gold Reversible bonding
Pressure pumping, intersection format, SPR imaging measurements of microfluidic hybridization channels.
* N/A: data not available; PS: polystyrene; PC: polycarbonate; PMMA: poly(methylmethacrylate); PP: polypropylene; PET: Polyethylene terephthalate; RT: room temperature; SPR: surface plasmon resonance. ǂ: The work was done by me as given in Chapter 3 (for ref. [94]) or Chapter 4 (for ref. [95]).
23
1.2.2 Microfluidic DNA hybridization with low-density probe arrays
Although the microfluidic system offers significant improvement over the
conventional bulk solution method for microarray hybridizations, two concerns
arise from the use of large chamber hybridization on high-density microarrays. As
described in the previous section, liquid flows over the large chamber have to be
carefully designed to achieve an equally distributed liquid movement across the
slide as well as to avoid trapping air bubbles in the chamber during filling. In
addition, because a huge number of probe features are packed into a small area,
great efforts are needed for data processing, normalization, and interpretation in
high-density microarray hybridizations [97]. In gene expression analysis, many
thousands of genes must be simultaneously monitored to create a global picture
of cellular function, and so high-density microarrays are needed. On the other
hand, in many gene diagnostic applications, once a relatively small number of
genes are identified, low-density microarrays could be designed to screen these
genes [98]. This approach of low-density microarray has been proved to be
reliable, cost-effective, and much faster in data analysis and interpretation [99-
105].
1.2.2.1 Low-density microfluidic microarray method with pin-spotted probes
The microfluidic method is suitable for incorporation into low-density DNA
microarray analysis. The use of microchannels instead of large hybridization
chambers alleviated the need for complicated chip design to achieve
homogeneous hybridization across the chamber area. The pin-spotting method
that has been an often used technique in the fabrication of DNA microarrays [43],
24
has also been used in microfluidic microarray experiments. Both straight
microchannels [84-87, 106-108] and serpentine microchannels [66, 88-90, 109]
have been designed. For example, Chung et al. constructed a low-density
microarray with 5 probe spots and they found a signal increase of up to 6-fold in
a straight microchannel with flow hybridization, as compared to static
hybridization (Figure 1-11) [87]. The authors also found that the hybridization
efficiency was further improved by introducing extensional strain from the change
of flow velocities inside the microchannel [87, 110]. Wei et al. proposed a
microchannel hybridization method with microtrenched serpentine channels, as
shown in Figure 1-12 [90]. Sample consumption was reduced to 1 µL and
hybridization time was as low as 500 s for oligonucleotide targets. The signal-to-
noise ratio was improved by 30-fold in the discrimination of 2 oligonucleotides
with one base difference (Figure 1-12b). In terms of probe spotting, either
commercialized small arrayers [88, 89, 106, 109] or even micropipettors [85, 86,
107] have been used.
25
Figure 1-11 (a) Schematic drawing of a straight hybridization channel and probe spots (unit: mm). The flow direction was from top to bottom. (b) Fluorescent images after 30 min hybridization. Left: hybridization results at u = 1 cm·s-1; right: hybridization results at u = 0 cm·s-1 (control). (c) Comparison of the averaged fluorescence intensities after hybridization. Reproduced from [87] by permission of The Royal Society of Chemistry.
Figure 1-12 (a) An illustration showing scrambled discrete plugs being swept over probe rows in the serpentine channel. The black arrow denotes the shuttle flow inside the microchannel. (b) The fluorescence images are from 500-s microfluidic hybridization (top row), 500-s static hybridization (center row) or 2-h static hybridization (bottom row). The left column represents the results from 20-mer PM targets, and the right column represents the results from 20-mer MM targets with single base-pair mismatch in sequence center. Reprinted with permission from [90], Copyright © 2005 Oxford University Press.
(a) (b) PM MM
(b) (a)
Unit: mm
(c)
26
1.2.2.2 Low-density microfluidic microarray method using microfluidic printing and the intersection approach
In low-density DNA microarray analysis, the conventional pin-spotting
method has been used to create dot-like probe arrays [43]. The performance of
the hybridization assay is thus heavily influenced by the quality of printed probe
spots. In practice, because the spotting solutions are open to air and the spotting
pins are very close to each other, the pin-spotting method may suffer from
problems such as splashing, uneven evaporation and cross-contamination [111].
Clearly, the ability to create probe spots of high homogeneity would be beneficial,
because this would simplify image analysis and considerably enhance the
accuracy of signal detection. When a spotting buffer such as saline sodium
citrate (SSC) solution is used, spot uniformity is often poor due to the
hydrophobic properties of the microarray chip surface. Supplementary chemicals
such as dimethyl sulfoxide (DMSO) can reduce solution surface tension, and
hence improve spot uniformity. But DMSO could also introduce new problems,
such as spot size increase, as shown in Figure 1-13a [112]. Moreover, during the
blocking and cleaning procedures in the chemical post-processing steps, the
remaining unreacted probe molecules could diffuse away and smear the slide,
giving rise to “comet tail” artefacts [19, 113, 114]. Furthermore, when
microchannel hybridization is to be used later with the spotted microarray,
additional devices such as bolts and clamps must be used to ensure that the
entire hybridization microchannel is well aligned to probe rows without liquid
leakage [90].
27
A simple and effective method is to use a microfluidic network to print
probe line arrays on a surface. In this technique, an elastomeric plate with
microchannel features is bound to another solid substrate to form the microfluidic
network. Upon flowing sample solutions through the microchannels, different
probe lines can be printed. For instance, species such as small molecules [115],
lipids [116-119], proteins [120-127], DNA [91-93, 96, 128, 129], and
nanostructures [95, 130-132], have been patterned on a variety of solid surfaces
(gold, glass, or polymer). Because the immobilization reaction between the
biomolecules and the surface is confined in microchannels, uneven evaporation
and splashing are prevented. In practice, less than 1 µL of reagent is needed to
fill through each microchannel and the solution can be kept at room temperature
for hours without drying out [94].
Figure 1-13b to d show examples of patterned biomolecules (protein and
DNA) or nanoparticles on solid surfaces using the elastomeric microchannel
plate. The surface was typically chemically-modified to anchor different types of
molecules. The bonding between the polymer channel plate and the glass slide
was reversible, and a homogeneous distribution of the probe molecules along the
region enclosed by microchannels was achieved. The resolution of microfluidic
line patterning can be very small down to the submicrometer scale [126].
Moreover, because the flow operation in each microchannel can be manipulated
individually, the probe immobilization step and subsequent processes such as
washing and blocking can be independently conducted, and the individual
channels can thus be used for condition optimization tests (Figure 1-13c). Cross-
28
contamination resulting from the diffusion of unreacted agents is avoided during
the washing and blocking steps. The microfluidic approach is simple and flexible
for the printing of low-density probe arrays.
Figure 1-13 (a) Fluorescent image of the hybridization of DNA probes (5 and 10 µM) spotted on activated glass slides with increasing concentration of DMSO. Reprinted with permission from [112], Copyright © 2003 Oxford University Press. (b) Fluorescence images acquired in Cy3 (green) and Cy5 (red) channels show the parallel microfluidic patterning of multiple DNA probes. Reprinted with permission from [128], Copyright © 2009 American Chemical Society. (c) A 16-channel microfluidic network was used to pattern 20-µm lines of decreasing antigen coverage onto a PDMS substrate (left line to right line) using solutions of different concentrations. The antigen was labelled with rhodamine. Reprinted with permission from [120], Copyright © 2000 American Chemical Society. (d) Cross-polarized optical image of [Mo3Se3
-]∞ nanowire patterns on glass substrate made with microchannel networks. Reprinted with permission from [131], Copyright © 2000 American Chemical Society.
Low-density probe line arrays created from microfluidic methods have
been used successfully for nucleic acid analysis [65, 91-94, 96, 129, 133, 134]. In
these applications, the intersection approach was used. This approach was first
(a) (b)
(c) (d)
29
proposed for immunoassays [121-124] and patterning nanostructures [130]. It
was soon expanded to DNA analysis [65, 91-93, 96] and lipid-protein interaction
studies [119, 135]. As shown in Figure 1-14a, probe lines were printed onto a
chemically-modified glass slide, which was reversibly sealed with the first
microchannel plate. After peeling off the first plate, a second channel plate used
for target recognition was then assembled with the same glass slide. Here,
microfluidic channels were arranged vertically and were orthogonal to the
preprinted probe lines. Sample molecules flowing through the microchannels
intersected with the probe line arrays. If specific or complementary probe
molecules were encountered, the target molecules were retained and rectangular
patches were thus formed. These patches could then be detected by surface
plasma resonance imaging (Figure 1-14b) [96], or more often, by fluorescent
flatbed scanner [65, 91-94, 129, 133, 134]. Compared with the pin-spotted
microarray (in Figure 1-13a), the final hybridization patches obtained from the
microfluidic microarray were more regular and well organized which facilitated
the subsequent image analysis.
30
Figure 1-14 (a) Intersection approach for performing an immunoassay on a surface with microfluidic network. (i) Patterning different antigen molecules along the horizontal lines on a solid substrate. (ii) The area of the substrate left unpatterned during step (i) is blocked with bovine serum albumin (BSA) to prevent nonspecific binding in subsequent steps. (iii) Antibodies flowing through the channels of a second microfluidic network locally bind to the patterned antigens. (iv) Reading the rectangular binding patches reveals the amount of antibodies present in the samples. Reprinted with permission from [124], Copyright © 2001 American Chemical Society. (b) SPR difference images showing hybridization of a RNA sample onto an array of surface-bound probe DNA. Hybridization of the target RNA onto the probe DNA array was indicated by a change in the reflectivity. Reprinted with permission from [96], Copyright © 2001 American Chemical Society.
The intersection approach on the microfluidic microarray is well suited for
parallel sample hybridizations. Unlike the pin-spotted low-density DNA
microarray, the use of probe line arrays alleviates the need for precise alignment
between the hybridization channels and the probe dots [66]. The method can be
used for the investigation or comparison of optimal assay conditions, and for high
throughput multi-sample analysis. Benn et al. compared the hybridization rates
of 60-mer oligonucleotides in 8 concentrations from 10 pM to 10 nM on one chip
(a)
(b)
(i)
(ii)
(iii)
(iv)
31
[91]. Situma et al. used a 16 ×16 array to detect two different low-abundant DNA
point mutations in oncogenes [93]. We have also used a 16 ×16 microfluidic
microarray device to test the effect of probe coverage, ionic strength and
incubation time on DNA hybridization all conducted on the same chip. With
optimized conditions, we successfully discriminated PCR product samples from
two fungal pathogen genomic DNA [94]. More details can be found in Chapter 3.
1.2.3 Microfluidic DNA microarray using centrifugal pumping
Microfluidic DNA microarray analysis with high sample throughput
demands parallel sample hybridizations in multiple microchannels, which raises
the question of finding an effective way to deliver liquid simultaneously. For the
conventional pressure-driven method, Huang and colleagues recently presented
a microfluidic device integrated with pneumatically-controlled microvalves and
micropumps for parallel DNA hybridizations [64]. This device has been applied to
analyse 48 different DNA targets (18-mer oligonucleotides derived from the
Dengue virus genes) simultaneously (Figure 1-15). However, the pressure-driven
method could be complicated because each microchannel has to be connected
to pump tubing and synchronization has to be considered to ensure parallel flows
[66]. Moreover, high pressure is required for liquid delivery in long and narrow
microchannels, and this in turn requires very tight sealing between the
microfluidic channel plate and the substrate. For example, a steel clamp was
used to hold and tighten a microfluidic microarray assembly using syringe
pumping [90].
32
Figure 1-15 (a) Photograph of the microfluidic chip containing shuttle-flow channels, microvalves and micropumps. The entire chip consists of three layers, the top and middle layer were made of PDMS containing microvalves, micropumps, and shuttle flow channels; the bottom layer was a glass substrate with gel pads on which DNA probes were immobilized. The shuttle flow hybridization was realized by controlling the gas ports 1, 2 and 3 automatically. (b) Hybridization specificity assay using four serotypes of the Dengue virus under shuttle flow conditions (frequency 2 Hz). Channels 1 to 4 indicated target DNAs (200 nM) of serotypes I to IV, with repetitions in channels 5 to 8, respectively. The duration of hybridization process was 90 s and washing time was 30 s. Reproduced from [64] by permission of The Royal Society of Chemistry.
Electroosmotic flow (EOF) is another microflow method that has been
used for parallel pumping of multiple channels [136, 137], albeit with multiple
electrode connections. The EOF flow control method depends not only on the
applied voltage across the microchannel, but also on the surface properties of
the microchannel as well as the low ionic strength of the buffered solutions [138].
The high salt concentration typically found in DNA hybridization buffers [19, 139,
140] may result in excessive Joule heating and electrolysis [85, 141-143]. These
effects will lead to drastic changes of the solution temperature and pH [144]
causing instability of hybridization and SNP discrimination performance.
Therefore, only a few reports were published applying EOF flow to microfluidic
DNA microarray analysis [85].
(a) (b)
33
An alternative liquid pumping method is to utilize the body force of the
liquid column itself, and such a force can be created under a centrifugal force
field. As compared to other technologies, centrifugal pumping is easy to
implement and is not sensitive to the physiochemical properties of the liquid. It
can move fluids in a parallel manner in multiple channels of a wide range of
sizes. Moreover, the compact disk (CD) and related industries including disk
materials, disk fabrication, signal reading and error correction, as well as rotor
driven/control systems have been well-developed over the past decades. With
the MEMS technology, the centrifugal microfluidic platform could be combined
with microarray technology to develop portable and point-of-care analysis
devices [145-148].
Centrifugal microfluidic platforms have been developed in many
applications including nucleic acid analysis, immunoassay in biomedical
diagnosis, cell lysis, separation and extraction, and environmental assays [39,
60, 106-108, 149-168]. Flow dynamics studies as well as microfluidic operation of
the liquid in rotating radial microchannels were also investigated [136, 169-178].
More works regarding the application of centrifugal pumping to microfluidics can
be found in several reviews [147, 148, 179, 180]. Reports on the microfluidic
microarray DNA hybridization achieved using the centrifugal pumping method are
listed in Table 1-2. The table summarizes the sample properties (sample types,
sample number, sample volume and concentrations), chip properties (chip
materials and chip bonding methods), and hybridization conditions (time and
temperature) of various experiments including those developed in Dr. Li’s group.
34
Table 1-2 Microfluidic DNA microarray hybridization conducted using centrifugal pumping.
Ref. Number of probe features
Sample volume
(μL)
Sample concentr
ation Sample type
Number of
samples
Hybridization time and
temperature
Chip materials
Substrate materials
Chip bonding Methods and applications
[60] 22000 60 N/A cDNA 1 17 h at 65°C Glass Glass Rubber and clamp Planetary centrifugal flow in the chamber.
[107] 6 3 0.1-100 nM oligonucleotides 1 3min PDMS glass Reversible
bonding Intergraded washing and block buffer chambers.
[106] 150 2 10nM 368-bp PCR amplicons 1 5 min at RT PDMS glass Reversible
bonding Integrated washing and block buffer chambers, differentiated 4 different Staphylococcus species.
[108] 32 0.35 25nM to 200 nM oligonucleotides 12 90 to 300s at
RT PDMS glass Reversible bonding
Reciprocating flow induced from rotation-pause operation of the CD device enhanced hybridization.
[129] ǂ 100 1 20nM oligonucleotides or PCR amplicons 100 10 min at
45°C PDMS glass Reversible bonding
Hybridization using intersection approach, detection of pathogen PCR amplicons. Up to 100 samples could be analyzed in parallel.
[65] ǂ 384 1 0.1nM for oligos
oligonucleotides or PCR amplicons 384 1 min at RT PDMS glass Reversible
bonding Hybridization using intersection approach, 384 × 384 hybridization assays have been performed.
[134] ǂ 100 1 N/A oligonucleotides or PCR amplicons 100 3 min at RT PDMS glass Reversible
bonding
3-min hybridization using intersection approach, discrimination of two pathogen PCR amplicons. Up to 100 samples could be analyzed in parallel.
[133] ǂ 96 1 0.5 nM oligonucleotides 96 3 min at RT PDMS glass Reversible bonding
Intersection approach hybridization in 3 min. Up to 96 samples could be analyzed in parallel.
* N/A: Data not available; RT: room temperature. ǂ: The work was developed in Dr. Li’s group, in which ref. [129] and ref. [134] are done by me as given in Chapter 5 and Chapter 6, respectively.
35
Although centrifugal pumping has been successfully exploited in many
microfluidic assays, its application to DNA microarray analysis is still rare [60,
106-108]. Bynum and Gordon used several rotors on a centrifugal platform to
induce reciprocal flows inside the DNA hybridization chambers [60]. After 17 h of
reaction, the measured signals were 10 times higher than those obtained from
the conventional static method [60]. Madou and co-workers developed a
chamber hybridization system, where the assembly of a glass slide and a PDMS
microfluidic chamber was placed on a CD support that could hold up to 5 slides
[106, 107]. Here, low-density spotted probe arrays were used and the
hybridization reagents were positioned to be pumped sequentially. The authors
demonstrated the discrimination of 4 clinically relevant Staphylococcus species
by the automated hybridization process in 15 min performed at room temperature
[106]. Li et al. presented a CD-like microfluidic device capable of generating a
reciprocating flow of DNA samples within the microchannels and demonstrated
its application in rapid DNA hybridization assays [108]. Here, centrifugal force
was used to drive the sample solution to flow through the hybridization channel
into a temporary collection reservoir while capillary force pulled the solution back
into the hybridization channel during the stopping period (Figure 1-16). The
sample hybridization time was reduced to 90s and the sample volume was as
low as 350 nL [108]. A theoretical model of this reciprocal flow by the interplay of
capillary and centrifugal forces has also been proposed [181].
36
Figure 1-16 (a) Schematic representation of a CD microfluidic device sealed with a glass substrate for DNA hybridization. It consists of a PDMS CD slab containing twelve DNA hybridization assay units with immobilized DNA probe arrays. (b) Schematic diagram of a single DNA hybridization assay unit. (c) Hybridization specificity tests with the CD microfluidic device. Top: Dengue virus serotype 1 targets. Bottom: Dengue virus serotype 2 targets. The CD device was rotated at 22 Hz for 3 s and then stopped for 3 s during the reciprocating process, with a duration of 90 s. Reprinted with permission from [108], Copyright © 2009 Elsevier Ltd.
The limited applications of centrifugal pumping for high throughput nucleic
acid microarray analysis could be attributed to the use of the radial-direction
structure design. Currently, almost all of the fluidic patterns in centrifugal
microfluidic platforms are fabricated in the radial orientation. Due to the
mechanical strength of materials and the demand of miniaturization, the length of
the microfluidic structure in the radial direction is limited. For example, if a
centrifugal platform is built on a 120-mm regular CD with a 15-mm centre spindle
hole, the length of a microfluidic structure cannot be more than 53 mm.
Therefore, the applicable space is very limited and the capillary effect may
(c)
(a) (b)
37
dominate the liquid flow process in microchannels. In addition, it is well known
that the centrifugal force increases with the increase in radius, and the average
velocity of the liquid is proportional to the radial extent of the fluid in a
microchannel [147, 156]. Such an increasing flow velocity in the microchannel
demonstrates the challenges and difficulties in the design of fluidic structures
[136, 169, 172]. Furthermore, the radial-like microfluidic structure cannot be
easily adapted to the intersection approach because centrifugal pumping
appears to be only exploited in one direction. Therefore, spotted probe arrays
have to be used for microchannel hybridization, which limits sample throughput,
and a lot of disk space is wasted.
Recently, our group developed a new microfluidic DNA microarray
method, in which the centrifugal advantages were exploited twice, first in the
radial microchannels, and then in the spiral channels [133]. The microarray
assembly consists of two CD-like PDMS chips as microchannel plates and one
92-mm glass wafer as substrate [129, 133, 134]. In the first step, the radial
channel plate is assembled with the glass wafer for printing the radial probe line
arrays; during the second step, the spiral channel plate is sealed against the
wafer with the printed probe lines after removing the radial channel plate. In both
steps, liquid flows in the channels are driven by centrifugal pumping obtained
from spinning the assembly. Because the spiral channels are nearly orthogonal
to the radial direction, sample flows thus intersect with the probe lines printed on
the disk and result in the formation of hybridization patches after complementary
target molecules are applied. The hybridization patches are in a rectangular
38
shape and are easy to be analysed. More details on the microfluidic DNA
microarray using centrifugal-pumping technology can be found in Chapters 5-7.
1.3 Research outlines
The proposed work is mainly focused on developing microfluidic
microarray methods for fast, low-volume, and high throughput nucleic acid
detection and discrimination.
Microfluidic microarray hybridization based on the intersection method
was first studied on glass slides using pressure-driven microflows. Optimal
conditions of probe printing as well as sample hybridization were examined for
the detection of both oligonucleotide and PCR product samples. A novel method
based on the interaction between gold nanoparticles and DNA molecules was
constructed for the discrimination between DNA targets with single base-pair
difference. Moreover, to get a better understanding of the mass transport and
surface hybridization in microfluidic systems, mathematical models were
constructed to predict the microfluidic hybridization behaviour with numerical
simulations.
Another research objective was to realize fast and high throughput DNA
analysis using centrifugal pumping technology. Compared with the stop-flow
method on the slide format, the hybridization time was shorten to <3min and up
to 100 samples can be analysed simultaneously. The microflow driven by
centrifugal pumping was further studied with fluid dynamics. The study describes
39
how device geometry, i.e. channel height and width, as well as rotation speed
influence liquid transport phenomena.
1.4 Dissertation structure
The main content of this dissertation is organised as per the structure
shown in Figure 1-17. Specifically:
In Chapter 1, an overview on the recent advances in microfluidic DNA
microarray hybridization is given. Part of the work has been
published in Analytica Chimica Acta (L. Wang and P.C.H. Li,
“Microfluidic DNA Microarray Analysis: A Review”, Anal. Chim.
Acta, 2011, 687, 12–27).
In Chapter 2, methods and technologies involved in the DNA microchip
fabrication and analysis are illustrated. The related instrumentations
are also introduced.
In Chapter 3, microfluidic probe spotting and DNA target hybridization
were conducted on glass slides using pressure-driven flow. The
intersection approach was used in the microfluidic hybridization. Up
to 16 samples from fungal DNA were detected. The results have
been published in the Journal of Agricultural and Food Chemistry
(L. Wang, and P.C.H. Li, “Flexible microarray construction and fast
DNA hybridization conducted on a microfluidic chip for greenhouse
plant fungal pathogen detection”, J. Agri. Food Chem., 2007, 55,
10509-10516).
40
In Chapter 4, room temperature discrimination of two fungal DNA
fragments with one base-pair difference was achieved with the
assistance of gold nanoparticles. The work has been published on
Biomicrofluidics (L. Wang, and P.C.H. Li, “Gold nanoparticle-
assisted single base-pair mismatch discrimination on a microfluidic
microarray device”, Biomicrofluidics, 2010, 4, 032209, page 1-9).
In Chapter 5, a circular glass disk was used as a microarray substrate
to employ centrifugal-pumping technology. Two polymer channel
plate, in radial and spiral direction, respectively, were designed for
microchip hybridization through the intersection approach. Up to
100 oligonucleotide samples can be detected in 3 min. The work
has been published in Analytica Chimica Acta (L. Wang, P.C.H. Li,
H.-Z. Yu, and A.M. Parameswaran. “Fungal pathogenic nucleic acid
detection achieved with a microfluidic microarray device”, Anal.
Chim. Acta, 2008, 610, 97–104).
In Chapter 6, with an improved design in channel geometry and target
labels, high-throughput discrimination of fungal DNA samples was
achieved on disk platform. The work has been published in
Analytical Biochemistry (L. Wang, and P.C.H. Li, “Optimization of a
microfluidic microarray device for the fast discrimination of fungal
pathogenic DNA”, Anal. Biochem., 2010, 400, 282-288).
In Chapter 7, experimental measurement and mathematical modelling
of centrifugal-pumping flow in spiral microchannels are described.
41
Section 7.3 was written based on the work of Dr. Kropinski from the
Department of Mathematics with the aid of my experimental data.
Part of the chapter has been published in Lab on a Chip (L. Wang,
M.-C. Kropinski, and P. C. H. Li, “Analysis and modeling of flow in
rotating spiral microchannels: towards math-aided design of
microfluidic systems using centrifugal pumping”, Lab Chip, 2011,
11, 2097–2108).
In Chapter 8, theoretical modelling and simulation of microfluidic DNA
microarray hybridization were studied. The manuscript is in
preparation (L. Wang, and P.C.H. Li, “Modeling of microfluidic DNA
microarray hybridization and its application to microchip design and
optimization”).
In Chapter 9, different aspects of this research work are summarized,
and an outlook on future directions is discussed as well.
In Chapter 10, detailed procedures on the use of COMSOL program
are listed. The procedures have been applied to the simulation of
the microfluidic DNA microarray hybridization kinetics as depicted
in Chapter 8.
42
Figure 1-17 The organization structure of this dissertation.
Applications to DNA analysis (4 chapters)
Simple slide format and pressure-driven flow
Circular disk format with centrifugal-pumping flow
Chapter 3: Concept of intersection
approach and optimization
Chapter 4: Further
improvement using
nanoparticles
Chapter 5: Application to
both oligos and PCR amplicons
analysis
Chapter 6: Improvement
and application to the fast SNP discrimination
Microfluidic Microarray DNA hybridization
Chapter 7: Modeling and simulation of centrifugal-
pumping microflow
Chapter 8: Modeling and simulation of
microfluidic DNA hybridization
Modeling and simulation of flow and hybridization (2 chapters)
For faster and higher throughput
assay
43
2: MICROCHIP FABRICATION AND DETECTION INSTRUMENTATION
2.1 Introduction
Microfluidics is a rapidly developing technology evolved from the well-
established microelectronics industry. The fabrication of microfluidic devices is
usually based on bonding two chip plates together where microfluidic structures
are created on one or both of the chip plates. Because of the great success in
semiconductor-related technologies, silicon and glass materials were first used
as substrates in making the microstructures by photolithography [138, 182, 183].
These materials such as glass are easily obtained and some of the properties,
such as high chemical inertness and/or excellent optical transparency, have been
very attractive in many applications [184, 185]. However, microstructure etching,
hole drilling, and chip bonding processes with these materials are costly and time
consuming [55, 138]. In addition, if microfluidic structures are used for patterning
surface-immobilized molecules on support chips, reversible bonding is preferable
for later applications of these chips with patterned molecules. Microfluidic devices
made in plastics or polymers offer unique advantages in addition to functionality
such as bio-compatibility, disposability and ease of mass production at low cost
[184, 186, 187]. A wide range of materials such as polycarbonates (PC),
poly(ethylene terephthalate) (PET), polypropylene (PP), polystyrene (PS),
44
poly(methyl methacrylate) (PMMA), and polydimethylsiloxane (PDMS) have been
structured with microfluidic channels. During the last decades, numerous
researches have been done with polymer microfluidic chips and some works
related to DNA microarray hybridization are listed in Table 1-1.
The fabrication of microstructures on polymer substrates can be achieved
using various methods including laser ablation, wire imprinting, hot embossing,
injection molding, and casting. Using the laser ablation technology,
microstructures can be imprinted directly onto the polymer substrate by moving a
focused laser beam across the surface and fluidic prototypes can be rapidly
produced with high accuracy and repeatability [63, 83, 90, 188]. However, the
requirement for a high-power laser instrumentation has limited the applications of
this process [189]. The wire imprinting method is a low cost method used to
create microfluidic channels on plastics but it suffers from low accuracy and the
inability to create complicated patterns [190]. Hot embossing and injection
molding have been widely used in structuring thermoplastic materials [72, 86, 89,
191, 192]. These methods involve the use of molding masters that contain the
desired microstructures to stamp (reverse-duplicate) patterns onto the substrate,
which are easy to be applied to the mass production of microchips.
Casting is a micro-replication method using silicone rubber to form
microfluidic structures. This technology, which is also named as soft lithography,
was developed by Whitesides and co-workers and has received much interest in
academic research due to its simplicity and low cost [193-195]. PDMS is the
most widely used silicone-based elastomer in casting microfluidic structures [70,
45
195, 196]. It is optically clear, non-toxic, and, in general, is considered chemically
inert. During soft lithography processes, a mixture of the elastomer precursor and
its curing agent is poured over a molding master. After curing at room
temperature or higher, the soft elastomer copy or replica is peeled off the
molding master. By simply sealing the PDMS plate with microstructures against a
planar substrate, a microfluidic network is formed without the use of thermal
bonding or high pressure. This PDMS casting technology was the method used
for fabricating microfluidic devices throughout my experiments.
2.2 PDMS-based Microfabrication Processes
The microfluidic devices in this thesis are assemblies from reversibly
bonding a flat glass chip to a PDMS plate with microstructures. The PDMS
channel plate is a replica from casting PDMS prepolymer solutions to a SU-8
coated Si master or an etched Si master. The fabrication of the master with
positive relief microstructures is based on the popular photolithography
techniques where a series of processes are involved (Figure 2-1).
At first, the surface of silicon wafers are cleaned thoroughly and a layer of
negative photoresist is deposited on the surface. The thickness of the photoresist
film determines the channel depth of the moulded chip. Upon UV exposure,
geometric shapes printed on a photomask are transferred to the photoresist
layer. The following development and hard-baking procedures leave polymerized
photoresist with the microchannel patterns on the silicon wafer. Figure 2-1
depicts the procedures of making a PDMS-glass microfluidic device with a
negative photoresist (e.g. SU-8). More details are illustrated in the following
46
sections. Furthermore, because dust could contaminate surface and reduce
product quality in most of the procedures, the concentration of airborne particles
has to be controlled to a low level using clean room facilities (Clean Air Products,
577 Series, Minneapolis, MN) as shown in Figure 2-2.
Figure 2-1 Sequence for fabrication of the microfluidic assembly using negative photoresist SU-8. (a) a plain silicon wafer (b) Si wafer coated with photoresist film; (c) wafer exposed to UV light through a photomask; (d) photoresist developed; (e) PDMS prepolymer solution casted on the SU-8 master; (f) PDMS channel plate peeled off; (g) PDMS channel plate bound to a glass chip to produce assembly.
Silicon substrate
Negative photoresist
PDMS channel plate
Photomask
UV light
PDMS-glass chip assembly
Layer deposition by spin coating
UV exposure
PDMS casting
Bonding with glass chip
Developing
(a)
(b)
(d)
(c)
(e)
(f)
(g)
Glass chip
Weir structure
Microchannels
47
Figure 2-2 Photograph of the softwall clean room facilities used for making microchip and a bionocular microscope for surface examination.
2.2.1 Surface preparation and layer deposition processes
The fabrication of microfluidic structures starts with the deposition of a
photoresist film on a silicon wafer. The wafer is a thin, round slice of silicon
crystal that has a diameter of 100 mm or more and it has a very flat surface.
Under exposure to oxygen, the silicon surface oxidizes to form silicon dioxide
Air filtration system
Reflective microscope
Nitrogen gas cylinder
Spin coater
UV exposure system
Vacuum pump
Hot plate
48
(SiO2). The adhesion of photoresist to the wafer surface is critical to the faithful
replication of the micropatterns [197]. In our practice, dust particles and films of
grease were washed away with acetone and isopropanol. Because water has a
higher affinity to SiO2 than organic photoresist, contamination from humidity
absorption is another major concern and the silicon wafers were further baked at
>100°C to get rid of surface moisture, which would otherwise weaken the
subsequent photoresist adhesion.
Once the wafer is prepared, a thin-layer of photoresist is applied. Spin-on
coating is the most common deposition techniques for producing a photoresist
layer on the surface of a Si wafer. Figure 2-3 illustrates the spin-coating
processes as well as the spin coater used in my experiments (WS-400, Laurell
Technologies Corporation, North Wales, PA). A controlled volume of photoresist
is dispensed onto a wafer and the wafer is then spun to produce a uniform
photoresist film. In our work, SU8 (SU8-50, MicroChem Corporation, Newton,
MA), an epoxy resin, has been used as the negative photoresist [198-200].
Because the SU-8 film will act as both a photoresist for pattern transferring and a
master layer for later PDMS casting, the thickness of the film has to be set to
match the final microchannel height. The control on film thickness depends on
the properties of the photoresist as well as rotation speeds as shown in Figure
2-3(f). For example, to achieve a layer of SU8-50 with 75-µm thickness, the spin
coater has to be rotated at a speed of 1600 rpm for 30 s. After the spin coating
process, the wafer with photoresist layer is baked at a temperature (95 °C) for
few minutes to remove most of solvent from the resin for later UV exposure.
49
Figure 2-3 (a)-(d) Illustration of the spin coating processes for the creation of the SU8 photoresist layer on a silicon wafer. (e) a spin coater with controller (f) rotation speed versus the thickness of the SU8 resin layer. The figure is adapted from MicroChem® product datasheet. SU8-50 and SU8-100 are different from each other in viscosity for different applications. In this thesis, SU8-50 has been used throughout.
2.2.2 Photolithography processes
Photolithography is the process of transferring geometric shapes from a
photomask to the photoresist layer on the surface of a silicon wafer. The process
involves, pattern drawing, pattern transfer by UV exposure, development; and
hard-baking.
As shown in Figure 2-1, micropatterns are transferred to the photoresist
layer on the silicon wafer by UV irradiation. The exposure is performed on a
(a) Dispense a controlled amount of photoresist
(c) Rapidly ramp - up the spin speed throwing off excess photoresist
(b) Allow the photoresist to spread across the wafer
(d) Spin at a higher speed (e.g. 2000rpm) to form a thin film of photoresist
Spin speed (×1000 rpm)
Film
thic
knes
s µm
)
1000 1500 2000 2500 3000
50
100
150
200
(e) (f)
50
standard UV aligner (Model LS-150-3, Bachur & Associates, San Jose, CA)
where a dose of 300–400 mJ·cm−2 measured at 365 nm is necessary for the
cross-linking of the photoresist (Figure 2-4 (a)). The photomask is a transparent
film with the micropatterns printed on it at high resolution. Because a negative
photoresist, SU8, has been used, the photomask contains an inverse copy of the
pattern which is to be created on the wafer (Figure 2-1(c)). Upon the exposure to
the UV light, the SU8 solution becomes polymerized, and more difficult to
dissolve than the unexposed SU8 in the later developing process. Then, a post-
exposure bake at 95ºC for 15min is required to accelerate the cross linking of the
epoxy resin to form a rigid structure with a high cross-linking density [198]. The
unexposed material is then removed with an organic solvent (SU8 Developer,
MicroChem Corp., Newton, MA) in the later developing process (Figure 2-4 (b)).
Figure 2-4 (a) Silicon wafer aligned with photomask under UV irradiation; (b) SU8 layer with microstructures on a 5-inch silicon wafer after the developing process.
Considering that the photomask is used to generate the microstructures, it
is obvious that its print quality determines the final microstructure quality on the
photoresist layer. Figure 2-5 compares the PDMS channel plate made from two
(a) (b)
51
photomasks. Two resolutions, 3368 dpi and 20000 dpi, respectively, were used
in printing the photomasks. As shown in the figure, lower resolution (3368 dpi)
printing results in serrated-shape channel sidewall (see Figure 2-5(a) and (b)),
while the higher resolution printing gives a much smoother microchannel
sidewalls (see Figure 2-5(c) and (d)).
Figure 2-5 Comparison of the quality of PDMS microchannels fabricated from two photomasks of different printing resolutions. (a) Photomask printed with 3368 dpi. (b) The microscopic image of the PDMS channel plate made from (a). (c) Photomask printed with 20,000 dpi. (d) The microscopic image of the PDMS channel plate made from (c).
2.2.3 Casting and bonding processes
Throughout this work, PDMS prepolymer (Sylgard 184, Dow Corning) was
used throughout for casting the microchannel plate. The use of PDMS offers
several benefits due to its characteristics. It is optically transparent down to 300
100µm
(a)
(c)
(b)
(d)
100µm
100µm
100µm
52
nm, chemically inert, and nontoxic after being cured and has highly thermal
stability (up to 300 °C) [201]. During the casting process, a solid weir is first built
around the edge of the Si wafer with the SU8 master layer (Figure 2-6 (a)). The
PDMS prepolymer solution is mixed with its curing agent in a particular ratio,
such as 10:1. Then the mixture is poured into the well to obtain the replica of the
pattern. The volume of the solution is calculated to obtain a polymer thickness
around 1~2 mm. After curing at 60°C for 4h or at room temperature for 24h, the
PDMS replica is peeled off from the master. To facilitate the peeling off process,
the Si master is treated with a small amount of releasing agents, such as
dimethyldichlorosilane (PlusOne™ Repel-Silane ES, GE Healthcare,
Buckinghamshire, UK).
During the bonding process, the cured PDMS plate could be overlaid
directly onto a glass substrate at room temperature for reversible bonding (Figure
2-6 (b)). Microchannels thus formed from the PDMS grooves and the glass
surface (Figure 2-1(g)). Solution reservoirs (1 mm in diameter) at both ends of
channels were made by punching holes on the PDMS plate with a flat-end
syringe needle. Although plasma oxidation could render the PDMS channels
hydrophilic property for easy filling of aqueous solutions in subsequent
experiments [202], the method was not used in our work because the sealing
between glass surface and the plasma-oxidized PDMS plate is non-reversible
[203, 204].
53
Figure 2-6 (a) SU8 master with weir structure around the wafer for PDMS molding. (b) Assembly of the PDMS microchannel plate with a glass disk.
2.2.4 Comparison of molding master made from SU8 or wet etching
In addition to the SU8 molding master depicted in the previous sections, Si
wafer itself could be fabricated into a master through wet chemical etching. With
the help of a positive photoresist, channel patterns are transferred onto the pre-
coated mask layer of the Si master. Upon using chemical etchant solutions, such
as HF, positive relief structures are created on the silicon wafer. The procedures
are shown in Figure 2-7.
(a) (b)
54
Figure 2-7 Sequence for fabrication of the microfluidic assembly using a positive photoresist and subsequent HF etching. (a) A clean Si or glass wafer. (b) Cr and Au masked Si wafer (c) The wafer in (b) is coated with positive photoresist. (d) The wafer in (c) is exposed to UV light through a photomask; (e) photoresist is removed; (f) The exposed metal mask is etched; (g) The exposed Si or glass etched; (h) The photoresist and metal is stripped; (i) PDMS prepolymer solution casted on the SU8 master; (j) The cured PDMS channel plate is peeled off; (k) PDMS channel plate is sealed to a glass chip to produce assembly.
The advantage of the Si master is its high mechanical strength and
durability. It has been reported for ~100 casting procedures without significant
degradation [205], while a SU8 molding master can only allow up to 30 PDMS
replicas to be made [193]. Nevertheless, SU8 is a popular structural material for
lab-on-chip applications [206]. When compared with the silicon or glass master,
PDMS-glass chip assembly
Silicon substrate
PDMS channel plate
PDMS casting
Positive photoresist coating
Metal layer sputtering
Photomask
UV light
UV exposure
Photoresist developing
Metal mask etching
Wafer etching
Removal of metal and photoresist
Bonding with glass chip
Cr & Au
photoresist
(a)
(b)
(c)
(d)
(e)
(f)
(i)
(g)
(h)
(j)
(k)
55
SU8 master shows superiority due to many advantages that are outlined as
follows.
First, the fabrication procedures of SU8 master are simpler and less
tedious. It takes only three steps in total to fabricate a SU8 master from a Si
wafer (Figure 2-1). On the contrary, the number of steps is doubled in making a
silicon master. Furthermore, because no metal layer sputtering instrument or
highly toxic HF solution is involved in creating the SU8 master, an in-lab modular
cleanroom could be used for rapid prototyping of micropatterns (Figure 2-2).
Furthermore, the use of SU8 resin layer gives better channel shape and
the PDMS replica shows better sealing with glass surface. The microchannel
structures on the silicon master are created from wet etching process. As shown
in Figure 2-8 (b), the growth direction of the microstructure is not completely
vertical. The lateral etching of the channel structure can be a significant
disadvantage if a microchannel with high aspect ratio is desired. Therefore, the
channel width is larger than the value on the photomask and the spacing
between channels has to be carefully calculated. Meanwhile, the SU8 molding
master has been known for making microstructures with high aspect ratios and
channel walls are almost vertical to the chip plate (Figure 2-8 (d)) [200, 207].
Furthermore, the bottom of the microstructure in the silicon master is near round
making the corresponding top part of the microchannel in the PDMS plate near
round (Figure 2-8 (b)). This feature affects the integrity of the sealing of the
PDMS channel plate to the glass surface. On the other hand, with proper
development, the bottom of the microstructure on the SU8 master can be made
56
flat (Figure 2-8 (d)) and the resulting PDMS channel plate will seal tightly with the
glass surface. No side leakage across spiral channels has been observed even
when the disk assembly was spun at 3600 rpm for 10 min.
Figure 2-8 Comparison of the Si masters and microchannels fabricated using positive and negative photoresist. (a) The reflective microscope image of the Si master fabricated from positive photoresist followed with KOH etching. (b) Surface profile of the microchannels in (a); (c) The reflective microscope image of the Si master fabricated from SU8 photoresist. (d) Surface profile of the microchannels in (c).
2.3 Surface modification to generate aldehyde-functionalized glass chips.
The glass substrates were chemically modified to produce aldehyde-
functionalized surfaces using an established procedure (See Figure 2-9) [208].
Briefly, plain glass slides were cleaned with 10% NaOH solution for 10 minutes at
(a)
(c)
(b)
(d)
57
~80°C. After being rinsed with distilled water, the slides were treated with a
piranha solution (70:30 v/v, sulphuric acid to 30% hydrogen peroxide) for 1h at
~80°C. The slides were then rinsed with water and dried under a stream of
nitrogen.
Figure 2-9 Surface modification to generate aldehyde-functionalized glass surface. Reprinted with permission from [94], Copyright © 2007 American Chemical Society.
The cleaned slides were treated with a mixture of ethanol: H2O:
aminopropyltriethoxyl silane (95:3:2 by volume) for 2h under stirring; rinsed with
95% ethanol and deionized H2O; dried under nitrogen and baked at ~120°C for
1h. The aminated glass slides were then immersed in 5% glutaraldehyde in a 10x
PBS (phosphate buffered saline) solution overnight and washed with acetone
and deionized H2O. After being dried in a nitrogen gas stream, the aldehyde-
modified glass slides were stored in a dark place at 4°C before probe printing.
OHOHOH
EtO
SiEtO
HO
NH2
OSiO
ON O
H
OSiO
ONH2
O O
H H
Clean glass surface
- H2O
- 3 EtOH
APTES
Glutaraldehyde
58
2.4 Immobilization of probe DNA.
The PDMS channel plate was sealed against the aldehyde glass slide to
form microchannels as shown in Figure 2-1(g). Then, 0.8 µL of probe DNA
prepared in the spotting solution (1.0M NaCl + 0.15M NaHCO3) was added into
the inlet reservoirs using a micropipette. The probe solution was filled through the
channels by applying vacuum pumping at the outlets or by centrifugal pumping.
With incubation at room temperature for 30 min, covalent Schiff linkage was
formed between the amine ends of the probe oligonucleotides and the aldehyde
groups on the glass surface (Figure 2-10) [209].
Figure 2-10 Covalent attachment of aminated probe DNA to aldehyde glass surface. Reprinted with permission from [94], Copyright © 2007 American Chemical Society.
After washing the microchannels with 1 µL of washing solution (0.15%
Triton-X 100, 1.0M NaCl and 0.15M NaHCO3), the PDMS channel plate was then
peeled off and the glass slide was chemically reduced with a NaBH4 solution
(100 mg of NaBH4 was dissolved in 30 mL 1x PBS and 10 mL 95% ethanol) for
15 min to reduce the Schiff linkage to the more stable C-N single bond (Figure
+ Probe AB
+ NaBH4
Aldehyde modified glass surface Covalent Schiff linkage between probe DNA and glass surface
Covalent C-N linkage between probe ssDNA and glass surface
3
OSiO
ON O
H
3
OSiO
ON N
33
CGCCAGAGATACCAAAACTC
6
OSiO
O
HN
HN
3
CGCCAGAGATACCAAAACTC
65
For further
hybridization
59
2-10). The glass chip was then rinsed with deionized water for 2 min and dried by
nitrogen gas.
2.5 Quantification of fluorescent image and data analysis
Following the hybridization and washing procedures, the glass substrate
with hybridization patches was scanned on a confocal laser fluorescent scanner
(Typhoon 9410, Amersham Biosystems, now GE healthcare) as shown in Figure
2-11. The excitation wavelength was 488 nm (for fluorescein-labelled targets) or
633nm (for Cy5-labelled targets) and the PMT (Photomultiplier tube) voltage was
set to 600V. The scanned image was collected at a resolution of 10 or 25 µm and
was analysed by the ImageQuant 5.2 program. In the data quantification
procedure, lines or boxes were manually drawn to cover the rectangular
hybridization patches on the image, and the average fluorescent intensity of the
patch was recorded in the relative fluorescent unit (RFU).
Figure 2-11 Typhoon 9410 confocal laser fluorescent scanner.
60
3: FLEXIBLE MICROARRAY CONSTRUCTION AND FAST DNA HYBRIDIZATION CONDUCTED ON A MICROFLUIDIC CHIP FOR GREENHOUSE PLANT FUNGAL PATHOGEN DETECTION
3.1 Introduction
Plant diseases from fungal, bacterial and viral organisms have caused
serious economic losses in greenhouse vegetable industry annually [210, 211].
Effective disease control requires rapid identification of disease microorganisms.
Currently, DNA microarray chips have been widely used in various applications,
such as expression profiling, genotyping and species characterization [212]. For
example, Xu et al. and Bordoni et al. have identified genetically modified soybean
and maize using oligonucleotide microarrays [213, 214]. Warsen et al. and
Ronning et al. discriminated between fish pathogens or closely related crops,
respectively, with microarray technology [215, 216]. The conventional DNA
microarrays are generally constructed either by on-chip synthesis of
oligonucleotide probes or by spotting of pre-synthesized probes on activated
substrates [111, 212]. For assays, samples containing the labelled target were
applied by manually spreading 10-50 µL of solutions on the microarray area for
hybridization, and the process usually requires long-time incubation up to 16
hours [19, 105].
61
Since the microfluidic method is capable of reducing the sample volume
and of accelerating diffusion and reaction kinetics, DNA hybridization has been
conducted in microfluidic channels [89, 90, 106, 217]. Moreover, probe
immobilization can also be achieved using microchannels. The resulting probe
line arrays can be used in subsequent microfluidic hybridization analysis with an
intersection method. For instance, Liu et al. designed a glass chip containing four
line arrays of oligonucleotide probes, and parallel hybridizations of human
genomic DNA targets were completed by using a second chip consisting of 4
sample microfluidic channels [218]. Similarly, Lee et al. created a 3×3 array on a
gold substrate and conducted microfluidic hybridizations to detect RNA
fragments derived from a transgenic plant [96]. Benn et al. studied the mass
transfer efficiency and hybridization kinetics inside microfluidic channels using
60-mer oligonucleotide samples on an 8 × 8 array [91]. Situma et al. has
achieved the detection of two different low-abundant DNA point mutations in
KRAS2 oncogenes using the intersection method with 16-channel microfluidic
chips [93]. In these pathogen detection or mutation studies, a small set of probes
is sufficient, and so a low-density DNA microarray can be constructed, as
opposed to the high-density microarrays needed for large-scale gene expression
profiling. Moreover, parallel sample analysis was achieved with microfluidic
hybridization as well as the intersection method.
To date, the application of the microfluidic microarray method to
agricultural problems has been limited. Here, we dubbed the method as
microfluidic microarray assembly (MMA) and a 16×16 DNA array was designed
62
to aim at fast assays. In this work, we use the MMA technique successfully to
identify three PCR products prepared from three fungal pathogens: Didymella
bryoniae, which causes gummy stem blight of greenhouse cucumbers; and,
Botrytis cinerea and Botrytis squamosa, which cause downy mildew and are
recognised as pathogens of overwintered salad crops [105]. The two Botrytis
amplicons are different from each other with only one base-pair difference in the
centre. We employed two 21-mer oligonucleotide probes and managed to
distinguish the PCR products with the microfluidic microarray method. It has
been demonstrated that 1.4 ng PCR products (~260bp, 1.4ng/µL, 1µL) were
detected at 50°C and one-base-pair discrimination was achieved in five minutes.
The results obtained from the printed glass slide in this work showed an
improvement over our previous work [105], in which targets were detected only
when the probes were spotted on an agarose-coated glass slide and were
hybridized overnight.
Here, the MMA method consists of 2 steps of assembly process, see
Figure 3-1. In the first step, channel plate 1 is assembled with the glass chip via
reversible bonding. Aminated DNA probes are introduced into the microchannels
and are immobilized on the glass chip. A line microarray of probes is thus
created. After peeling off plate 1, channel plate 2 is then assembled with the
same glass chip. The sample solution that flows through the microchannels will
intersect the probe line arrays and hybridization is accomplished in a few
minutes. Both the creation of probe microarray and hybridization process in
microfluidic channels are capable of reducing the sample volume (< 1 µL) and of
63
preventing from evaporation and cross-contamination. In this work, it was found
that the MMA method not only provides a flexible probe creation method, but also
enhances the detection sensitivity and achieves differentiation of various
greenhouse pathogens.
Figure 3-1 The microfluidic microarray method using straight microchannels. (a) The creation of a DNA probe line array on an aldehyde-modified glass slide via straight microchannels. (b) The hybridization of DNA samples in straight channels orthogonal to the straight probe lines printed on the glass slide. Reprinted with permission from [94], Copyright © 2007 American Chemical Society.
3.2 Experimental
3.2.1 Materials.
All chemicals and solvents were purchased from BDH Tech Inc (Toronto,
Canada), unless stated otherwise, and used without further purification. 3-
Aminopropyltriethoxyl silane (APTES), 50% glutaraldehyde, sodium dodecyl
sulphate (SDS) and Triton X-100 were obtained from Sigma-Aldrich. Ultra-pure
water (18 MΩ·cm-1) was obtained from an Easypure RF purification system
(Dubuque, IA). Negative photoresist (SU8-50) and its developer were purchased
from MicroChem Corporation. An elastomer base, Sylgard® 184 silicone and its
1) Sealed against an aldehyde glass chip
2) Flow of aminated DNA probe solution
Channel plate 1 horizontal channels
1) Peel off channel plate 1.
Line arrays of DNA probes
Channel plate 2 vertical channels
1) Sealed against the glass chip with line microarray
2) Flow of DNA sample solution
Sample Hybridization
1) Peel off PDMS channel plate 2
Detection results
2) Scan with confocal fluorescence scanner
2) Reduction of Schiff base linkage Probe
immobilization
(a)
(b)
64
curing agent used to make polydimethylsiloxane (PDMS) were obtained from
Dow Corning Corporation (Midland, MI). The plain 3"×2" glass microscope slides
were purchased from Fisher Scientific Company (Ottawa, ON, Canada). All other
chemicals and solvents were purchased from BDH Tech Inc (Toronto, ON,
Canada) and used without further purification.
All oligonucleotides were synthesized and modified by Sigma-Genosys
(Oakville, ON, Canada). The sequences of probe oligonucelotides were designed
to detect two greenhouse plant pathogens, Botrytis cinerea (with probe AB and
ALB) and Didymella bryoniae (with probe AD) [105, 219]. The probes were
modified with an amine group at the 5’-end. In AB and AD molecules, this amine
group was spaced from their DNA sequences with a C6 linker, while a C12 linker
was used in ALB. Dual labelled probe ADF, which has the same DNA sequence
as that of probe AD, has its 3'-end also labelled with fluorescein. The probe was
used as a marker during probe immobilization and sample hybridization.
Oligonucleotide samples, B’F and FD’ which are complementary to the
sequences of probe AB and AD, respectively, were labelled with fluorescein at
the 5’-end. CD’ has the same sequence with FD’ but was labelled with Cy5 dye
at the 5’-end. The sequences of oligonucleotides used and their acronyms were
listed in Table 3-1.
65
Table 3-1 Oligonucleotides and PCR products used in this study
Acronym Length Sequence (5'-3')
AB 21-mer NH2-(CH2)6 –CGC CAG AGA ATA CCA AAA CTC
ALB 21-mer NH2-(CH2)12 –CGC CAG AGA ATA CCA AAA CTC
AD 22-mer NH2-(CH2)6 –CGC CGA TTG GAC AAA ACT TAA A
ADF 22-mer NH2-(CH2)6 –CGC CGA TTG GAC AAA ACT TAA A-Fluorescein
FB’ 21-mer Fluorescein or Cy5 –GAG TTT TGG TAT TCT CTG GCG
FD’ 22-mer Fluorescein or Cy5 –T TTA AGT TTT GTC CAA TCG GCG
CD’ 22-mer Cy5–T TTA AGT TTT GTC CAA TCG GCG
FB’P 264-bp
FBN’P 264-bp
FD’P 259-bp
Genomic DNA samples were extracted from cucumber–dextrose broth of
Botrytis cinerea, Didymella bryoniae and Botrytis squamosa at Agriculture and
Agri-Food Canada [105]. Three PCR products (FB’P, 264 bp; FD’P, 259 bp;
FBN’P, 264bp) were amplified and labelled with fluorescein from the 3 species,
respectively. The concentration of FB’P and FD’P was ~40 ng/μL (~250 nM),
while that of FBN’P was lower at about 6 ng/μl (~40 nM). The central sequences
of the sense strand of FB’P and FD’P are complementary to the sequences of
probe AB and AD, respectively, while FBN’P has one base-pair difference
(TTT:ATA instead of TAT:ATA in the center) from that of FB’P [220].
… –A AAT TCA AAA CAG GTT CGC CGC–…
Fluorescein –…–T TTA AGT TTT GTC CAA TCG GCG–…
Fluorescein –…–GAG TTT TGG TTT TCT CAG GCG–
… –CTC AAA ACC AAA AGA GTC CGC–
Fluorescein –…–GAG TTT TGG TAT TCT CTG GCG–
… –CTC AAA ACC ATA AGA GAC CGC–…
66
3.2.2 Fabrication of PDMS channel plates.
A 2"×2" PDMS channel plate was fabricated using the established
photolithographic method, as described in Section 2.2.2 [193]. The channel
pattern was designed using Visual Basic (Microsoft) and was printed on a
transparency to create the photomask at a resolution of 3368 dpi. The PDMS
channel plate consists of 16 parallel microchannels. The width of the straight
channels was 300 µm and the channel height was 30 μm. The length of the
straight section of each channel was 30 mm. Solution reservoirs (1 mm in
diameter) at both ends of channels were punched on the PDMS channel plate
using a flat-end syringe needle. The images of the assembly of a 2"×2" PDMS
channel plate on a 3"×2" glass slide are shown in Figure 3-2.
Figure 3-2 The images of the assembly of a 2"×2" PDMS channel plate on a 3"×2" glass
slide. (a) Image of16 channels filled with blue-dye solutions in horizontal direction. (b) Image of 16 channels filled with green-dye solutions in vertical direction. Reprinted with permission from [94], Copyright © 2007 American Chemical Society.
(a) (b)
67
3.2.3 Probe line printing, sample hybridization and result read-out by fluorescent scanning.
The glass substrates were chemically modified to produce aldehyde-
functionalized surfaces and aminated probe DNA was spotted in line array with
the PDMS channel plate. The detail procedures have been shown in Chapter 2.
In DNA target hybridization, the glass chip with probe line arrays was
covered with a PDMS channel plate. The straight channels were orthogonal to
the printed probe lines on the slide (as shown in Figure 3-1b). The DNA samples
(oligonucleotides or PCR products) were prepared in the hybridization buffer (4x
SSC + 0.2% SDS, unless stated otherwise). The PCR products were denatured
at 95°C for 4 min and then quickly cooled in an ice-water bath just before
hybridization. 1.0-µL DNA targets were added to the inlet reservoirs using an
automatic pipettor. Sample solutions in different reservoirs were then pumped
into channels by vacuum suction simultaneously applying at the 16 outlets. The
flow of DNA targets and their binding on the immobilized probes in a
microchannel was shown in Figure 3-3. Two methods were used to control the
hybridization temperature inside the microchannels. In the continuous-flow mode,
a Peltier device (CP1-12715, Thermal Enterprises, NJ) was placed under the
glass slide assembly and the hybridization temperature was adjusted by tuning
the voltage applied to the Peltier device. In the stop-flow incubation mode, the
assembly was incubated in a humidity box placed in an oven at a specified
temperature. Hybridization was achieved between complementary DNA targets
in solution and probe lines at the intersections, showing the hybridization patches
68
of 300 µm × 300 µm. The microchannels were rinsed immediately with 2-µL
hybridization buffer following hybridization.
Figure 3-3 Microfluidic hybridization of target DNA strands (in red) in the parabolic liquid
front to the probe DNA strands (in blue) immobilized on the glass chip surface. Reprinted with permission from [94], Copyright © 2007 American Chemical Society.
Following the hybridization and washing procedures, the glass slide was
scanned on a confocal laser fluorescent scanner (Typhoon 9410, Molecular
Dynamics, Amersham Biosystems). The resolution is 25 µm. The excitation
wavelength was 488 nm or 633 nm for fluorescein-labelled or Cy5-labelled
samples, respectively. The photomultiplier tube (PMT) voltage was set to 600 V.
The scanned image was analyzed by ImageQuant 5.2 software. In the data
quantification procedure, square frames (13 pixels ×13 pixels) was overlaid on
the square hybridization patches in the image. The average fluorescent signals of
the 169 pixels were measured in relative fluorescent unit (RFU).
69
3.3 Results and discussion
3.3.1 Flexible probe immobilization without spotting.
In conventional microarrays using the robotic spotting method, it usually
took 8-16 h for probe immobilization to complete after spotting [19]. To reduce
solvent evaporation during this process, a humidity chamber was used and
DMSO might have to be added in the probe solution. The latter may either
increase the spot size on the slide or reduce the actual amount of DNA fixed on
the solid support [112]. On the contrary, in the microfluidic printing method, the
probe solution, which was confined to the PDMS microchannels, would not dry
out even in several hours. Furthermore, shrinking of the channel dimensions to
micro-scale decreased the diffusion time and hence the incubation time needed
to complete probe immobilization [59, 63]. To study the effect of immobilization
time on the signal intensity, dual-labelled oligonucleotide probe (ADF) was flowed
through and incubated in the microchannels for different durations. It was found
that the fluorescent intensity was higher with immobilization time of 30 min than
with 15 min, as shown in Figure 3-4a. When immobilization time was more than
30 min, the signal intensity from immobilized probes did not increase by more
than 3%. Thus, 30 min was considered enough to achieve effective probe
immobilization.
70
Figure 3-4 Probe immobilization. (a) Effect of ionic strength of spotting solutions and immobilization time on the ADF signal. The probe line arrays were made by incubating 0.8 µL of 25-µM ADF prepared in 1.0M NaCl (grey bar) or 0.1M NaCl (white bar) in microchannels at different durations. The slide was chemically reduced and then washed with distilled water. The fluorescent signals were measured by scanning the slide at 488nm. (b) The fluorescent image of ADF probe lines (vertical green stripes) printed on the glass slide using different immobilization times. The brighter the probe lines, the stronger the fluorescent signals. Reprinted with permission from [94], Copyright © 2007 American Chemical Society.
The effect of solution ionic strength on probe immobilization was also
studied with the same chip. In the spotting buffer containing 1.0 M NaCl, we
observed a greater ADF signal intensity, as compared to that obtained in 0.1 M
NaCl (Figure 3-5a). Our observation is consistent with the previously reported
findings by Peterson et al. that single-stranded DNA is less adsorbed using a
buffer of a low salt concentration [221]. This is because the charged DNA strands
are better electrostatically shielded under the high ionic strength condition [222],
and so it could be easier for aminated oligonucleotides to come into contact and
to react with the aldehyde groups on the glass surface.
Flow direction
Probe ADF in 1.0M NaCl
20 mm
Probe ADF in 0.1M NaCl
(b)
0
6000
12000
18000
24000
30000
15 30 45 60 90 120
Immobilization time of Probe ADF (min)
Imm
obili
zati
on s
ign
al (
RFU
) in 1.0M NaClin 0.1M NaCl
(a)
71
Figure 3-5 Sample hybridization. (a) The immobilization signal of various ADF probe solutions (0.8-µL) at different concentrations (10 to 400 µM) that were incubated in microchannels for 2 h. After washing, the slide was scanned at 488nm. (b) The hybridization signals resulted from the above probe lines. Complementary oligonucleotides (CD’) labelled with Cy5 (100 nM, prepared in 1xSSC + 0.2%SDS) was hybridized to the ADF probe lines for 10 min. After washing, the slide was scanned at 633nm. (c) Overlaid dual-channel image of the same glass slide showing both printed probe lines (vertical green lines) and square hybridization patches (red) at intersections. ADF probe immobilization was achieved in duplicate at each concentration. Reprinted with permission from [94], Copyright © 2007 American Chemical Society.
The effect of the probe concentration on probe coverage was also studied.
As shown in Figure 3-5a, the fluorescent intensity is much higher using 25 µM
than 10 µM of ADF, but the rate of increase is reduced when the probe DNA
concentration goes from 25 to 400 µM. It was found that the signal obtained at
25-µM DNA probes has reached around 60% of the value obtained from 400-µM
probes. Apparently, the amount of immobilized oligonucleotides kept increasing
with the higher probe concentration, and the results did not generate an
optimized probe concentration for microfluidic probe printing. Further
(c) 17 mm
10 25 50 100 200 400
100-
nM D
’C
Probe ADF at different concentrations (μM)
Probe flow direction
0
5000
10000
15000
20000
25000
30000
0 50 100 150 200 250 300 350 400ADF probe concentration (µM)
Imm
ob
iliz
atio
n s
ign
als
(RFU
)
0
20000
40000
60000
80000
10 25 50 100 200 400
ADF probe concentration (µM)
Hyb
rid
izat
ion
sig
nal
s (R
FU)(a) (b)
72
experiments were carried out by the measuring the hybridization signals obtained
from these probe lines. Here, complementary oligonucleotides (CD’) labelled with
a second fluorescent tag, Cy5, were used to distinguish the hybridization signals
(at 633 nm) from the immobilization signals (at 488 nm). It is clear from Figure
3-5b that the hybridization signal has reached its highest value with probe lines
prepared with 50-µM ADF, and the amount of hybridized samples decreased
when higher probe concentrations were used. Our observations were consistent
with the findings from Le Berre et al. and Peterson et al. that higher probe density
on the glass surface could reduce the efficiency of duplex formation and the
kinetics of target capture procedure [112, 221]. The decreased hybridization
signals from probe lines at high concentrations might be due to steric constraints
resulted from the high probe density on the glass substrate. Accordingly, 25-µM
probe was chosen as a compromise for both signal sensitivity and reagent
savings. The surface coverage of the DNA probes on the surface was also
estimated. This was achieved by establishing a calibration graph correlating the
fluorescence signals to the concentrations of ADF solutions when they were
completely filled inside channels. It was found that the fluorescent intensity of the
probe lines created with 25-µM ADF was comparable to that of a 0.5-µM ADF
solution, leading to the surface density of 5 × 1011 strands/cm2, which was
comparable to the value of ~3 × 1012 strands/cm2 obtained in a recent study
[221].
73
3.3.2 Fast hybridization of multiple DNA samples.
Two sets of fluorescein-labelled oligonucleotide samples, FB’ and FD’, at
3 different concentrations, were hybridized to pre-printed oligonucleotide probe
lines of AB and AD at room temperature for 10 min. As shown in Figure 3-6a,
fluorescent patches showing successful hybridization occur at the intersections
between the vertical printed probe lines and horizontal microchannels filled with 3
samples of different concentrations (1, 10, 100 nM). It was found that 1μL of 1-
nM FB’ and FD’ could be detected. The signal-to-noise ratio of 1 nM of FB’ and
FD’ were 5.6 ± 0.4 and 4.1 ± 1.1, respectively. Good specificity of hybridization
was obtained, as shown in Figure 3-6b. The non-specific binding signals
remained low even at a high sample concentration of 100 nM. The hybridization
kinetics was found to be faster in microchannels than that in bulk solutions [89].
This experiment has demonstrated the detection of 2 different oligonucleotide
samples (1μL, at three concentration of 1, 10 and 100 nM) after hybridization at
room temperature for 10 min. Moreover, the patches formed in microfluidic
hybridizations are regular in shape, which is an important feature for subsequent
image analysis.
74
Figure 3-6 Hybridization of oligonucleotide samples to printed probe lines. (a)
Fluorescent images of the hybridizations of oligonulceotides (FB’ and FD’ prepared in 1X SSC + 0.2% SDS) with probe line arrays for 10 min at room temperature. (b) Histogram showing the fluorescent intensities of hybridization versus non-specific binding at various sample concentrations. The grey bars represent the signals of samples hybridized with their complementary probe sequences, i.e., FB’ with AB, or FD’ with AD; the white bars represent the non-specific binding. The error bars describe the standard deviations of the signals from 5 or 7 hybridization patches. Reprinted with permission from [94], Copyright © 2007 American Chemical Society.
After experiments with oligonucleotide samples, two PCR products (FB’P,
264 bp; FD’P, 259 bp) which were amplified from plant fungal cultures were
tested. Usually, the hybridization for PCR products requires higher temperature
and longer duration as compared to oligonucleotide samples. Therefore, in
conventional DNA microarray experiments, overnight incubation of samples in a
thermostated chamber is needed [223]. Accordingly, denatured PCR products
were hybridized to probe lines at 50 °C, which was at a temperature lower than
their melting temperature (~66 °C) [17]. Moreover, the results obtained from
different hybridization conditions were compared: the first set was carried out by
continuous flowing of samples for 5 min and the second and the third sets were
conducted by stop-flow incubation for 30 min or overnight. As shown in Figure
0
500
1000
1500
2000
2500
3000
3500
1nM-B'F 1nM-D'F 10nM-B'F
10nM-D'F
100nM-B'F
100nM-D'F
Hyb
rid
izat
ion
sig
nal
s (R
FU) With complementary probes
With non-complementary probes
AD AB AD AB AD
1-nM D’F
1-nM B’F
10-nM D’F
10-nM B’F
100-nM D’F
100-nM B’F
3 mm (a) (b)
75
3-7a, it was found that longer hybridization time gave stronger signals, but the
30-min hybridization signal for FB’P has reached ~75% of that obtained from
overnight hybridization; it was ~82% for FD’P. However, the two targets were
already distinguished clearly by using 5-min hybridization at continuous flow of
the PCR product samples, which suggested that the hybridization rate was
enhanced greatly by the microfluidic flow. Figure 3-7b depicts the fluorescent
images of the results obtained for hybridizations at 3 different flow/incubation
conditions. In the case of long-time hybridization, a humidified box had to be
used and the condensation of water vapour on the chemically modified glass
slide might create variations on the background signals shown in the fluorescent
images. However, in the case of 5-min flow, a low background was observed
because a short hybridization time was used and so no humidified box was used.
As compared to our previous work [105], where FB’P and FD’P were detected
with pin-spotted DNA microarrays, the new MMA method simplified the probe
creation step (no agarose, no spotting), reduced the sample volume (from 50 μL
to 1 μL) as well as shorten the hybridization time (from overnight to 5 min.). In
addition, multi-sample hybridizations were achieved all on the same chip.
76
Figure 3-7 Hybridization of PCR products to printed probe lines. (a) Fluorescent signals from the hybridization of 2.6-ng pre-denatured PCR products (FB’P and FD’P) at 50 ºC for 5-min flow, 30 min incubation and overnight incubation, respectively. (b) The fluorescent images corresponding to the left histogram of hybridizations of 2 samples to 7 probe lines. Reprinted with permission from [94], Copyright © 2007 American Chemical Society.
3.3.3 Effect of probe tether length and one-base-pair-difference discrimination.
In this work, we also studied the effect of different probe tether length on
the hybridization efficiency of PCR products with printed probe lines within
microfluidic channels. In a study reported by Shchepinov et al., they found that
the use of a longer tether in the immobilized probe led to a higher hybridization
signal [224]. In our hands, two aminated probes with 2 different tethers were
used: probe AB (with a C6 tether) and probe ALB (with a C12 tether), see Figure
3-8.
0
200
400
600
800
1000
B'PF D'PF B'PF D'PF B'PF D'PF
Hyb
ridi
zati
on s
ign
als
(RFU
)With complementary probesnon-specific binding
(b)
AB AD AB AD AB AD AB
Overnight incubation
30-min incubation
5-min flow
D’PF
B’PF
D’PF
B’PF
D’PF
B’PF
(a)
30-min incubation
Overnight incubation
5-min flow
77
Figure 3-8 The immobilized oligonucleotide probe with C6 or C12 tether as spaced from the glass substrate. Reprinted with permission from [94], Copyright © 2007 American Chemical Society.
After immobilizing these two probes (AB and ALB) under the same
conditions, the PCR products were hybridized to them at 50 °C for 5 min. As
shown in Figure 3-9 (a) and (b), probe ALB gave a ~3-fold higher hybridization
signals than probe AB when the PCR products (1.4 ng and 2.6 ng) were applied.
This finding is consistent with Shchepinov’s result, which is attributed to a less
steric hindrance where the longer tether probe is spaced farther away from the
glass substrate. However, a longer tether led to a decrease in the hybridization
specificity, and more non-specific binding (signals from FD’P) was observed,
shown as small black bars in Figure 3-9(a).
OSiO
O
HN
HN
Surface loaded C6 tethered probe DNA
3 5DNA
OSiO
O
HN
HN
3 5 DNA
Surface loaded C12 tethered probe DNA
78
Figure 3-9 Hybridization of PCR products to probes having different tether lengths. (a) Fluorescent signals from hybridization of PCR products (1.4 ng and 2.6 ng) to probes with 2 different tether lengths. (b) The fluorescent image corresponding to the left histogram of hybridizations of samples to 5 probe lines. (c) Effect of probe tether length on discrimination of PCR products with one-base-pair-difference. Fluorescent signals come from the fluorescent patches of three PCR products (FB’P, FBN’P and FD’P, 1.4ng for each). The small black bars come from the non-specific binding signals of FD’P and they are too low to be seen on probe AB. The error bars describe the standard deviations of the signals from 5 duplicated tests. (d) The fluorescent image corresponding to the left histogram of hybridizations of 3 samples to 5 probe lines. In all cases, the DNA targets were hybridized by continuous-flow method for 5 min at 50 ºC. Reprinted with permission from [94], Copyright © 2007 American Chemical Society.
The lower specificity obtained when a longer tether probe is used has an
impact on our study of the discrimination between two PCR products with one-
base-pair-difference. These two PCR products (FB’P, 264 bp; FBN’P 264bp)
were from two closely related subspecies, Botrytis cinerea and Botrytis
squamosa, respectively. They differ in only one base-pair at the centre of the
0
50
100
150
200
250
300
350
With probe AB With probe ALB
Hyb
ridi
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ign
als
(RFU
) B'PFB'NPFD'PF
0
200
400
600
800
1000
1200
Hyb
ridi
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on s
ign
als
(RFU
)
(b)
AD AB ALB
2.6 ng/μL D’PF
1.4 ng/μL B’PF
2.6 ng/μL B’PF
1.4 ng/μL D’PF
AB ALB
(d)
AD AB AB ALB ALB
B’PF
BN’PF
D’PF
(c)
(a)
2.6 ng/μL
B'PF
D'PF
2.6 ng/μL
1.4 ng/μL 1.4 ng/μL
79
264-bp long sequences, see Table 3-1. The duplex formed between denatured
FBN’P and probe AB had a one base-pair mismatch (TTT:ATA instead of
TAT:ATA) in the centre of the PCR product. The melting temperature of the
mismatch duplex was calculated to be 5°C lower than that of the matched
duplex. The hybridization results were shown in Figure 3-9c and Figure 3-9d.
Although probe ALB gave higher hybridization signals for FB’P, the discrimination
between FB’P and FBN’P was lower. In terms of differentiation between FBN’P
and FB’P, it was found that the longer tethered probes captured more
mismatched DNA targets; the shorter tethered probe gave both lower non-
specific binding and a better discrimination between the two PCR products. It can
be seen from Figure 3-7c that the discrimination ratio of FBN’P over FB’P is 15%
for the probe AB, while the ratio becomes worse to ~60% for the longer tethered
probe ALB. Therefore, by using the short tethered probes, we have
demonstrated the capability of the MMA method to discriminate between low
amounts of PCR products (1.4ng) with one base-pair differentiation.
80
3.4 Conclusion
In this work, the microfluidic microarray assembly (MMA) method was
employed in which flexible probe array creation and fast DNA sample
hybridization were conducted in microchannels. The hybridization could be
fulfilled in minutes at the intersections between the sample channels and printed
probe lines. The process conducted in microfluidic channels was capable of
reducing the sample volume (< 1 µL), and of preventing the liquids from
evaporation and cross-contamination. It was demonstrated that one femtomole
DNA (1nM, 1µL) of oligonucleotide samples were detected in 10 minutes at room
temperature. The microfluidic method was also applied for greenhouse plant
fungal pathogen detection of two ~260-bp PCR products, Botrytis cinerea and
Didymella bryoniae, (1.4 ng/µL, 1µL, at 50 °C for 5 min). For the first time, fast
discrimination (in 5 min) between two 260-bp PCR products with one-base-pair-
difference was achieved with a discrimination ratio of 15%. It is demonstrated
that the MMA method provides the advantages of flexible probe creation, low
sample volume, good spot homogeneity, and fast hybridization rate, as applied to
agricultural problems.
81
4: GOLD NANOPARTICLE-ASSISTED SINGLE BASE-PAIR MISMATCH DISCRIMINATION ON A MICROFLUIDIC MICROARRAY DEVICE
4.1 Introduction
For many years, gold nanoparticles (GNPs) have been used in the fields
of bio-diagnostics based on different formats [225]. In the first format, GNPs are
labelled to thiol-modified oligonucleotide probes which are used for the specific
recognition of target DNA. Signal read-out is achieved based on the unique
properties of GNPs. For example, scanometrical methods were developed using
the catalytic effect of GNPs on silver staining [226-228]; a series of molecular-
beacon methods were constructed based on the strong quenching effect of
GNPs on fluorescence [229-232]; colorimetric methods were also developed
based on the hybridization-induced inter-linkage of GNP-labelled probes [233-
236].
Recently, the non-covalent binding of ssDNA to GNPs was discovered,
and this was applied to DNA analysis [237]. GNPs are usually stabilized via a
layer of adsorbed negative ions (such as citrate ions) on their surface [238], while
they are synthesized by citrate reduction of HAuCl4 in aqueous solutions [239,
240]. It was found that uncoiled ssDNA could bind to GNP surface through
attractive van der Waals forces between the bases and the negatively charged
82
GNPs [237]. This binding is tight and GNPs could be released only upon the
hybridization with complementary target DNA. Therefore, in the second format,
GNPs acted as competitors to discriminate between complementary and non-
complementary DNA targets. Subsequent duplex detection can be achieved
either by colorimetric method from salt-induced GNP aggregation or by
fluorescence-resonance-energy-transfer method [237, 241-243]. Since no thiol
modification is involved in this second format, the method is simple and it has
been used in oligonucleotide detection, single-base mismatch discrimination, as
well as aptamer-based applications in bulk solutions [237, 243-246].
Microfluidic technology offers the advantages of less sample consumption
and fast detection processes. Nevertheless, its applications to GNP-assisted
bioanalysis are mostly focused on immunoassay with GNP catalyzed silver
staining [247]. In terms of DNA analysis, a polydimethylsiloxane (PDMS)
microfluidic device was developed for DNA discrimination by hybridization-
induced GNP aggregation-related colour change [235]. However, only 15-mer
oligonucleotides were analyzed and concentration was tested at 6 µM.
In this work, two GNP-assisted methods for DNA analysis were evaluated.
In the first method, the glass surface was modified with a submonolayer of
GNPs, and probe DNA molecules were then applied and allowed to bind to
GNPs. The nanoscale spacing between GNPs on the surface resembles the
distance created from dendrimer coating, which allows better hybridization
efficiency and higher signals [112, 248]. In the second method, we found that
even when the probe DNAs were immobilized on a glass surface, they are also
83
able to hybridize with the GNP-bound target DNAs in solutions. GNP will then be
released and washed away. We thus combined the use of GNPs with microfluidic
technology and applied the method to the detection of PCR amplicons.
Moreover, it was found that the mismatched target DNAs showed less
hybridization with immobilized probes, as compared to the matched ones.
Therefore, the mismatched DNAs remained bound with GNPs in solution and
were washed away later. We have successfully achieved the room-temperature
discrimination of two 260-bp PCR products with one base-pair difference using
this second method.
4.2 Experimental
4.2.1 Fabrication of the PDMS-glass microchip.
PDMS channel plates consisting of 16 parallel microchannels were
fabricated, as described in Section 2.2.2.
4.2.2 DNA samples
Oligonucleotides were synthesized and modified by Sigma-Genosys
(Oakville, ON, Canada) or International DNA Technologies (Coralville, IA). The
21-mer DNA probes were modified with an amine group at the 5’-end. Target
oligonucleotides are either 21-mer or 50-mer with Cy5 dye at the 5’-ends. The
central 21 bases are complementary (perfect match) or one-base-pair mismatch
to the sequences of the probe molecules.
84
Two 264-bp PCR products (or amplicons) were amplified from genomic
DNA samples, and were labelled with Cy5 dyes as previously described [134].
The central sequences of the sense strand of perfect matched PCR amplicons
are complementary to the sequences of probe molecules, while the mismatched
amplicons have one base-pair difference from that of the perfect matched ones.
4.2.3 Depositing GNP layers on glass surface using microfluidic method.
In the first method of our work, a GNP sub-monolayer was coated on the
glass surface before probe immobilization. Here, the microchip with aminated
glass substrate was used. GNP solutions (20 nm in average diameter, Sigma Life
Science) at different volumes were flowed through the microchannels. GNPs thus
deposited onto the aminated glass surface and formed strip-like layers along the
microchannels. The uncovered amine groups on the glass surface were capped
by acetyl groups by filling through the microchannels with acetic anhydride [249].
After washing the microchannels with 95% ethanol followed with citrate buffer
solutions, the microchip was dried out for subsequent probe immobilization.
4.2.4 Preparation of DNA-GNPs conjugates.
In the second method of our work, sample DNA molecules were bound to
GNPs to form DNA-GNP conjugates before hybridizations. GNP solutions (5 nm
in average diameter, Sigma life science) were added into the DNA samples
(oligonucleotides or PCR products) in water. In the case of PCR products, the
mixtures were incubated at 95ºC to denature and uncoil the DNA chains and so
ssDNA molecules were produced for binding to GNPs non-covalently. The DNA-
85
GNP conjugates were snap-cooled in an ice-water bath before the hybridization
experiments. All the conjugate solutions were diluted to the desired concentration
before hybridization.
4.2.5 Probe line printing, sample hybridization and result read-out by fluorescent scanning.
The procedures of probe DNA printing, target hybridization, and signal
read-out are similar to the previous work depicted in Section 2.2.3.
4.3 Results and discussion
4.3.1 GNP-modified surface and its application to microarray DNA hybridization
In microarray technology, the effect of surface coverage on probe
orientation and sample hybridization signals has been studied by many groups
[221, 224, 250, 251]. It was found that probe density is a governing factor for the
amount of hybridization as well as for the kinetics of the target hybridization. In
order to maximize hybridization signals, the probe density should be high
enough. However, at a very high probe density, the steric hindrance by the
adjacent DNA probe molecules reduces the target capture efficiency and
hybridization kinetics. On the other hand, at a lower probe density, probes are
more accessible to targets and hybridization kinetics is faster [221]. Based on
this finding, different approaches have been proposed to achieve a controllable
probe density by adjusting the spacing of surface functional groups (such as –
CHO or –NH2) used for probe immobilization. For instance, nanoscale distance
86
was created by either dendrimer coating or self-assembled dendrimers on glass
surface [112, 248]. By covalent binding between modified DNA probes and the
pendant functional groups on the dendrimer molecules, probe density was
reduced and higher detection sensitivity was achieved in hybridizations.
In this work, we made use of a sub-monolayer of GNPs on glass surface
to achieve a nanoscale-controlled spacing for subsequent probe immobilization.
As depicted in Figure 4-1, GNPs deposited on the aminated glass surface are
bound electrostatically between the positive amine surface and negative GNP
surface. Due to the inter-particle repulsion from the surface negative charges of
GNPs, a self-assembled sub-monolayer forms on the glass surface [252, 253].
The “saturated” coverage was measured at ~30% by different groups and the
spacing has been calculated at around 12.5 nm between GNPs [254, 255]. This
spacing is comparable to the length of 21-mer oligonucleotides (~12nm) [256].
Since probe DNA molecules are to be immobilized onto the GNPs, the DNA
strands will also be separated in nanoscale spacing.
87
Figure 4-1 Schematic diagram of the formation of the nanoscale-controlled spacing between oligonucleotide probes using GNPs. (a) Protonated amine groups on the APTES-treated glass surface. (b) GNPs, with adsorbed citrate ions, are then deposited to the aminated glass surface and form a submonolayer. (c) The remaining non-reacted amine groups are deprotonated using a pH 11 buffer and masked by acetic anhydride (Ac2O). (d) When oligonucleotides probe DNA solutions flow through the submonolayer, the amine groups at the 5’-end of the molecules will bind only to GNPs which are well spaced out on the glass surface. Reprinted with permission from [95], Copyright © 2010 American Institute of Physics.
We used a microfluidic method to deposit GNP sub-monolayer on glass
surface on a 16-microchannel PDMS chip. The confinement of solutions in
microchannels resulted in strip-like GNP layers on the glass surface. The inset in
Figure 4-2 shows pink strips after flowing through 10-µL GNP solutions. The pink
colour of the layer reflects an unaggregated status of gold nanoparticles on the
surface. It is because GNPs will induce a shift of the surface plasmon band and a
visual colour change (from red to blue) when they are in close contact [252].
Grabar et al. achieved different particle coverage by incubating with GNP
solutions for different times [254]. Unlike the bulk solution method, microfluidic
1) pH11 buffer
2) Ac2O 3) Citrate
buffer Amine-labelled probes
(b)
(c)
(a)
(d)
88
method offered flexibility to immobilize different amount of GNPs on the same
glass slide and deposition was very fast due to the high surface-to-volume ratio
in microchannels. The more solutions flowed through the channels, the more
nanoparticles were deposited on the surface and showed deeper colour. From
Figure 4-2b, it can be seen that the strips from applying 2-µL solutions is barely
visible. It was found that the GNP binding on glass withstood the later acylation
and washing steps.
Figure 4-2 Different modified surfaces for hybridization experiments. (a) Image of an APTES modified glass slide with immobilized GNP strips (b) Magnified image of the glass slide with insets showing (i) Flow through 2-µL GNP solutions, (ii) Flow through 10-µL GNP solutions. The glass slide was first treated with APTES solution to create an aminated surface. Then a PDMS channel plate was sealed against the glass slide. GNP solutions in different amounts were filled through 8 microchannels. The deposition of GNPs onto the aminated surface resulted in the pink strips. The rest of the microchannels were left empty to keep the glass surface aminated. The images were taken after washing the microchannels and peeling off the PDMS plate. Reprinted with permission from [95], Copyright © 2010 American Institute of Physics.
The effectiveness of GNP submonolayer coated surface was evaluated
with the hybridization of oligonucleotides samples. With the PDMS-glass
microchip, probe DNA solutions were flowed through microchannels (vertically
oriented) and incubated with the GNP strips on the glass slide. DNA probe
molecules that are conjugated with amine groups at 5’-end were introduced for
(a)
(b) (i)
(ii)
89
immobilization to GNPs [252]. After probe immobilization, the PDMS channel
plate was peeled off and the second PDMS plate with horizontally oriented
microchannel was sealed against the glass slide for sample hybridization at the
intersection between the horizontal microchannel and vertical probe strips. This
orthogonal or intersection microfluidic method has been used in our previous
work and many other groups [91, 93, 94, 96, 129, 134]. The resulting
hybridization patches from oligonucleotides complementary perfect match
(PM) and one-base mismatch (MM) are shown in Figure 4-3. For comparison,
sample hybridization with probes immobilized on aminated glass surface without
GNPs was also shown. It can be seen that the hybridization signals on GNP-
modified surface are higher than those on aminated surface, and more GNP
coverage obtained by using more GNP solutions has resulted in even higher
signals.
Figure 4-3 Fluorescent images of the hybridization results from (a) 21-mer and (b) 50-mer target oligonucleotides at different modified surfaces. The targets are either complementary perfect- match (PM) or one-base mismatch (MM) in the sequence center with the probe DNA molecules. (a) Hybridization of Cy5 labelled 21-mer targets. The probe DNA lines were printed microfluidically on: aminated glass surface, on surface modified by flowing through 2-µL GNP solutions, and on surface modified by flowing through 10-µL GNP solutions (b) Hybridization of Cy5 labelled 50-mer targets. The probe DNA lines were printed microfluidically on: aminated glass surface, on GNP modified surface with Ac2O treatment to cap remaining amine groups, and on GNP modified surface without AC2O treatment. Reprinted with permission from [95], Copyright © 2010 American Institute of Physics.
Probe DNA lines PM MM
Aminated surface
GNP-2uL
GNP-10uL
10 nM 50-mer oligonucleotide
targets
10 nM 21-mer oligonucleotide
targets
(a) (b)
Aminated f
GNP modified, but no AC2O treatment
GNP modified with AC2O treatment
Probe DNA lines PM PM
90
GNP modified surface offers advantages of nanoscale spacing in DNA
probe immobilization, and resulted in higher hybridization signals, and our results
have confirmed this. However, the method currently can only be applied to
oligonucleotide targets that have a similar sequence length with the probes, but
not to longer DNA targets. As shown in Figure 4-3b, when 50-mer targets were
applied, the hybridization signals (the middle image) are much lower than those
from aminated surface only (the top image). This is because the dangling end of
DNA strand with the fluorescent labels could drop on the GNPs and the
fluorescence signals are thus be quenched [229]. The bottom image in Figure
4-3b also shows the hybridization results on GNP modified surface but without
acetic anhydride treatment. Because GNPs formed a sub-monolayer and cannot
cover all the amine groups on the glass surface, the probe DNA molecules can
still bind to the aminated surface non-covalently and hybridize with the targets
later [257, 258]. These duplexes were not quenched by GNPs and can thus be
detected, though with a weaker signal than obtained from the purely-aminated
surface (top image).
4.3.2 GNP-DNA conjugates and its application to single-base-pair discrimination
The use of nanoscale spacing surface for DNA probe immobilization
enhanced hybridization signals. However, the discrimination ratio between
perfect-matched and mismatched DNA could not be improved, and longer
oligonucleotide samples could not be detected efficiently through the use of the
91
GNP modified surface. To solve this problem, a different strategy of using GNPs
was employed in the second part of our work.
Figure 4-4 (a) GNP-DNA conjugates from the incubation of target DNAs with gold nanoparticles. (b) Perfectly matched target DNAs desorbed from GNPs and hybridized to the surface immobilized probes. (c) Mismatched DNAs remained bound to GNPs and were washed away through microfluidic method. Reprinted with permission from [95], Copyright © 2010 American Institute of Physics.
The principle of GNP-assisted DNA discrimination was illustrated in Figure
4-4. This is based on non-covalent binding between GNPs and targets, in
competition with the specific interaction between the targets and the immobilized
probes. This non-covalent binding is thought to act between GNPs and nitrogen
bases on the DNA strands, and is resulted from both hydrophobic interaction and
electrostatic adsorption [259]. Here, target DNA labelled with fluorescent
molecules were first incubated with GNPs solutions at high temperature. The
solution of GNP-DNA conjugates was then applied to pre-printed DNA probe
lines on the glass slide through microfluidic method. Because the base-pair
interaction between matched DNA chains is strong, sample DNA molecules
could desorb from GNPs and hybridize with the immobilized probes. The read-
GNP Labelled
target DNA Glass slide with hybridized DNA
DNA bound to
GNP
(a) (b)
Washing away GNPs
(c)
Glass slide with immobilized probes
92
out of the hybridization signals were achieved read-out through the fluorescent
labels on the sample DNA molecules. On the contrary, mismatched DNA showed
much less binding energy with the probes and thus still bound with GNPs. The
conjugates were washed away in the microfluidic flow and discrimination was
made.
Figure 4-5 (a) Images of hybridized patches of perfect-matched (PM) and mismatched (MM) target oligonucleotides in triplicate. Here, the oligonucleotides were pre-incubated with GNPs (5 nm) at different ratios. (b) Discrimination ratios between PM and MM duplexes. The discrimination ratios were calculated by dividing the signal of PM DNAs with that of MM DNAs (The higher ratio, the better). (c) The fluorescent hybridization signals from the images in (a), and the results at Oligo/GNPs = 1:1 are expanded and shown in the right inset. Reprinted with permission from [95], Copyright © 2010 American Institute of Physics.
The proposed GNP-assisted discrimination method was first verified with
two 50-mer oligonucleotides with one-base difference in centre. The samples
hybridized with the same probe molecules to produce two types of duplexes,
(a) Hybridization of oligonucleotides
(c)
PM
No GNPs added
MM PM MM PM MM
Oligo:GNPs = 2:1
(b)
0
400
800
1200
1600
Oligo:GNPs = 1:1
Fluo
resc
ent
inte
nsity PM
MM
Oligo:GNPs = 1:1
0
4000
8000
12000
16000
20000
No GNPs added Oligo:GNPs = 2:1
Oligo:GNPs = 1:1
Fluo
rese
cent
inte
nsity
(R
FU)
PM
MM
Ratio of PM/MM oligos
0
2
4
6
8
10
No GNPsadded
Oligo:GNPs= 2:1
Oligo:GNPs= 1:1
Dis
crim
inat
ion
ratio
s
93
namely the perfectly matched (PM) duplex and the mismatched (MM) duplex. As
shown in the images in Figure 4-5a, without pre-incubation with GNPs, the
hybridization signals from mismatched targets are very close to those obtained
from complementary targets. The discrimination ratio, which is the hybridization
signal ratio of PM duplexes over MM duplexes, is around 1.4. With the use of
GNP conjugates instead of free DNA molecules, the discrimination ratio was
raised up to 6.8. A clear discrimination between two oligonucleotides was
observed from the images in Figure 4-5a.
The effect of the molar ratio between GNPs and target oligonucleotides
on hybridization signals and discrimination ratios was also investigated. The
molar concentration of GNPs can be calculated from total gold concentration as
well as the size of the GNPs [260]. For 5-nm diameter GNPs in our study, the
particle molar concentration is around 86 nM. Conjugates of different GNP/DNA
ratios were thus prepared in this manner. Figure 4-5c compares different
hybridization intensities from conjugates of different Oligo/GNP ratios. It was
found that the more GNPs were incubated with DNA samples, the weaker were
the hybridization signals. The ratio at Oligo/GNP = 1:2 even resulted in non-
detectable hybridizations. This observation could be explained by the relatively
strong binding between GNPs and DNA as well as the slow kinetics of
desorption. Despite the reduction in the fluorescent intensities, GNPs does
enhance the discrimination of single base-pair mismatch, and the hybridization
signals are still adequate as shown in both the images and the inset graph in
Figure 4-5c.
94
Figure 4-6 (a) Images of hybridized patches of perfect-matched (PM) and mismatched (MM) PCR products in triplicate. Here, the amplicons were pre-incubated with GNPs (5 nm) at different ratios. (b) Discrimination ratios between PM and MM amplicons. The discrimination ratios were calculated by dividing the signal of PM DNAs with that of MM DNAs (The higher the ratio, the better). Reprinted with permission from [95], Copyright © 2010 American Institute of Physics.
This nanoparticle-assisted microfluidic method was applied to the room-
temperature discrimination of two related Botrytis subspecies, B. cinerea and B.
squamosa [105]. The two PCR amplicons differ in only one base pair in the
middle of the 264-bp long sequence [134]. Although these two targets were
already discriminated in our previous work, thermal stringency up to 62˚C has to
be applied to the microchip for washing away mismatched duplexes [134]. In this
work, amplicons were first incubated at 95˚C with GNPs. This incubation serves
for two reasons: one is to denature double-strand amplicons as the usual
procedures and another is to promote the subsequent binding of ssDNA to
GNPs. The later snap chilling procedures (at 4 ˚C) prevented the renaturation of
ssDNA molecules. Although both of the two complementary strands were bound
to GNPs and co-existed in the same solutions, they can be still used as samples
for later microarray hybridization because the renaturation between two long
ssDNA strands with high complexity is much slower than that between long
ssDNA and short oligonucleotide probes [256]. The discrimination ratio without
Ratio of PM/MM PCR amplicons
0
5
10
15
20
25
30
35
No GNPsadded
DNA:GNPs= 4:1
DNA:GNPs= 2:1
Dis
crim
inat
ion
ratio
s
(a) Hybridization of PCR amplicons PM MM PM MM PM MM
(b)
No GNPs added
DNA:GNPs = 4:1
DNA:GNPs = 2:1
95
the use of GNPs is ~3.6 while it goes up to ~27.7 with the assistance of
nanoparticles (Figure 4-6b). Compared with the discrimination ratio of ~6.7 using
temperature stringency at 50°C (results not shown), the GNP-assisted method has
not only improved discrimination, but also alleviated the need of high temperature
and related heating devices in the microfluidic chip applications.
4.4 Conclusion
In this work, two GNP-based DNA analysis methods using a microfluidic
device are presented. In the first method, fast coating of a submonolayer of
GNPs with nanoscale spacing on glass surface was achieved using a microfluidic
chip. Probe DNA molecules were then immobilized onto the GNP submonolayer.
The hybridization efficiency of the target oligonucleotides was improved due to
the nanoscale spacing among probe molecules. In the second method, target
DNA molecules, oligonucleotides or PCR amplicons, are first bound to GNPs and
then hybridized to the immobilized probe DNA on a glass slide. With the aid of
GNPs, we have successfully discriminated, at room temperature, between two
PCR amplicons (derived from closely related fungal pathogens, Botrytis cinerea
and Botrytis squamosa) with one-base-pair difference. DNA analysis on the
microfluidic chip avoids the use of large sample volumes, and only a small
amount of oligonucleotides (8-fmol) or PCR products (3-ng) was needed in the
experiment. The entire procedure is accomplished at room temperature in an
hour, and apparatus for high temperature stringency is not required.
96
5: FUNGAL PATHOGENIC NUCLEIC ACID DETECTION ACHIEVED WITH A CD-LIKE MICROFLUIDIC MICROARRAY DEVICE
5.1 Introduction
DNA microarrays are typically constructed either by on-chip synthesis of
oligonucleotide probes or by spotting of pre-synthesized probes on activated
substrates [111]. The applications of microfluidics to the fabrication of
microarrays are relatively recent and it has been reported that microchannels
provide a means to increase the hybridization rates over passive hybridization
using cover slips [85, 87, 89].The applications in which the DNA hybridizations
are conducted in microfluidic channels include the detection of oligonucleotides
[72, 84, 87, 261], bacterial DNA [109], clinical diagnostics of colorectal cancers
[86, 217], and single-nucleotide polymorphism studies [89, 106].
For the immobilization of DNA probes, microchannels have been used to
prepare line arrays, which were subsequently hybridized with DNA samples
delivered via a second set of microchannels (that orthogonally intersect with the
probe line arrays). Such a 2-D microarray method has been applied to the
analysis of oligonucleotide and PCR product samples [91, 93, 96, 262]. In these
reports, either capillary effect or pressure pumping was used to generate
microflows. We have also created a 16 × 16 microarray on rectangular glass
97
slides for fungal DNA analysis with pressure-pumping flows, see Chapter 3 and
Chapter 4.
Based on the unique design of spiral microchannel from our group, we
have been working on DNA microarrays fabricated on CD-like glass chips. With
the probe lines first created using radial channels, DNA hybridizations occurred
in the spiral channels that orthogonally intersected with the radial probe lines
[133, 263]. Liquid delivery in these channels (96 in total) can conveniently be
achieved by centrifugal pumping, in both the radial and spiral directions; this
method of liquid pumping has previously been applied only in the radial fashion
[106]. In this work, we apply this approach for the detection of two plant fungal
pathogens, Botrytis cinerea and Didymella bryoniae, which have caused serious
economic losses in greenhouse vegetable industry annually [210]. Traditional
methods of identification disease organisms can be slow and inconclusive, thus
preventing the timely implementation of the appropriate control measures.
Molecular diagnostic methods for plant pathogen include antibody-based and
nucleic acid-based approaches. The latter have increasingly been used in recent
years due to rapidity, simplicity and sensitivity [105, 264]. In this paper, coupled
with the proposed all-microfluidic assembly for probe immobilization and
hybridization, this DNA-based method has demonstrated the advantages of
flexible construction of oligonucleotide probe arrangements and multiple sample
capability in the subsequent target hybridizations. Moreover, we have achieved
accurate and faster hybridizations using smaller amount of samples (1 µL) than
in the conventional microarray method (30-50 µL).
98
5.2 Experimental
5.2.1 Materials
CD-like glass disks were purchased from Precision Glass & Optics (Santa
Ana, California, USA). They are 4” in diameter and were drilled with a 0.59”
centre hole. All other chemicals and materials are similar to those depicted in
Section 2.2.1. The sequence of the probes, marker, and targets are shown in
Table 3-1.
5.2.2 Surface modification of glass chips and the fabrication of PDMS channel plates
The glass substrates were chemically modified according to the procedure
shown in Section 2.3. The fabrication of PDMS channel plates has been depicted
in Chapter 2. As shown in Figure 5-1, the size of each PDMS plate is 92 mm in
diameter and ~2mm in thickness. The depths of the radial and spiral
microchannels were 25 or 50 μm, respectively. The solution reservoirs (1 mm in
diameter) were created on the channel plates by punching the PDMS chip using
a flat-tip syringe needle. All reservoirs were numbered for easy tracking during
solution introduction.
99
Figure 5-1 Assemblies of the PDMS channel plates with glass disks. (a) The circular channel plate with radial microchannels. All the channels (100 in total) were filled with dye solutions; (b) The image of an equi-force spiral channel plate assembled with a glass disk. Here, 30 out of 100 spiral microchannels, three in a group, were filled with dye solutions. The scale bar represents 10 mm.
5.2.3 Probe line array creation
As shown in Figure 5-2(a), the radial PDMS channel plate was sealed
against the aldehyde glass disk. 0.8-µL probe DNA solution was added into the
inlet reservoirs by a micropipette. The probe solution was filled through the
channels by spinning the assembly at 300 rpm for 10 min. With incubation at
room temperature for a certain time, covalent Schiff linkage was formed between
the amine ends of probe oligonucleotides and the aldehyde groups on the glass
surface [209]. After immobilization, the residual solutions were spun off the radial
channels at 3600 rpm for 10 min. The PDMS channel plate was then peeled off
and the glass disk was reduced with a NaBH4 solution (100 mg of NaBH4
dissolved in 40 mL of 0.75x PBS + 25% ethanol + 0.15% Triton X-100) for 15 min
10 mm
(a) (b)
100
to reduce the Schiff linkage to the C-N single bond. The glass disk was then
rinsed with deionized water for 2 min and dried by nitrogen gas stream.
Figure 5-2 Schematic diagram of probe immobilization and sample hybridization using CD-like microfluidic microarray assemblies. (a) Probe printing procedure: an array of radial probe lines was created on an aldehyde-modified glass disk using a radial channel plate. (b) Hybridization procedure: the hybridization occurring at the intersections between the spiral channels and radial probe lines, shown as colored patches in the last circle. Reprinted with permission from [134], Copyright © 2010 Elsevier Ltd.
5.2.4 Sample hybridization with spiral channel plate assembly
In DNA target hybridization, the glass disk printed with radial probe lines
was covered with a spiral PDMS channel plate (as shown in Figure 5-2(b)). The
direction of spiral channels was just orthogonal to the printed probe lines on the
disk (as shown in Figure 5-2(b)). 1.0 µL of fluorescein–labelled target DNA
solutions were added to the inlet reservoirs by a pipette. The spiral PDMS
channel plate assembly was spun at 700 rpm for 3 min on a rotating platform for
continuous liquid delivery. If the hybridization time was more than 10 min, the
channels were first filled by spinning at 700 rpm for 2 min, followed by stop-flow
incubation for a definite duration, unless stated otherwise. In this case, the whole
1) Sealed against a radial channel plate
2) Flow through DNA probe solutions.
Aldehyde glass disk with a central hole
Peel off PDMS radial channel plate
Radial probe lines printed on glass disk
Spiral Channel plate with microchannels
1) Sealed against the glass disk with probe lines
2) Flow through DNA sample solution
Hybridization at probe-line-channel intersections
1) Peel off spiral channel plate
Hybridization results on the disk
2) Scanned by fluorescent scanner
Spun the assembly to drive flows inside channels
(a)
(b)
101
assembly was removed from the rotating platform, put in a humidified container,
and was incubated in a temperature-controlled oven for duration up to 150 min.
Following hybridization, the CD-like assembly was spun at 3600 rpm for 10 min
to dry the channels and no further channel washing was needed. After removal of
the PDMS channel plate, the glass disk was rinsed with 2× SSC + 0.2% SDS for
1 min, then with 2× SSC for another 1 min, and was then dried in a nitrogen
stream.
5.2.5 Quantification of fluorescent image and data analysis
The glass disk with hybridization patches was scanned and analysed
following the procedures depicted in Section 2.5. The image was collected at a
resolution of 10 µm.
5.3 Results and discussion
5.3.1 Improvements in the design and fabrication of channel plates
In this work, radial and spiral channel width was designed to be 180 μm
and 80 μm, respectively. The spacing between spiral channels was 120 μm.
Since the samples in the spiral channels could only be hybridized at their
intersections with the probe lines, the dimension of the hybridization patches was
defined by the width of the radial and spiral channels, i.e. 180 μm × 80 μm. In the
previous reports, both radial and spiral channel widths were 60 μm, leading to the
dimension of the hybridization patches to be 60 μm × 60 μm [133, 263]. Though
the channel width in the new design has been increased, the dimension of the
disk was kept to be 92 mm in diameter by moving the inlet reservoirs closer to
102
the centre of the disk than in the case of the old design. With the wider channels
in the new design, the liquid transport from the inlet reservoir could be initiated at
a lower spinning speed (300 rpm for radial channels and 700 rpm for spiral
channels). On the contrary, with the 60-μm wide radial channels in the old
design, a spin rate of 500 rpm was used for liquid transport, and care must be
taken to avoid the liquid being spun out radially over the disk surface from the
inlets, rather than inside the radial channels. In the case of the 60-μm wide spiral
channels, the spinning speed must be at least 1800 rpm in order to obtain a
steady liquid flow inside the microchannels.
5.3.2 Hybridization of oligonucleotide samples on the CD-like MMA
After the radial probe lines were printed on the disk, the spiral channel plate was
sealed against the disk for sample delivery. As shown in Figure 5-3(a), a section
of the PDMS spiral channel plate that was sealed against the disk was shown, in
which 6 sample channels orthogonally intersected with 3 printed probe lines on
the disk. After hybridization, a series of rectangular patches were formed at the
intersections (see Figure 5-3(a) for schematic, and Figure 5-3(b) for actual
results, respectively). In one experiment shown in Figure 5-3(b), the probes AB
and AD were distributed alternatively and radially on the glass disk during the
probe immobilization step. With the assembly of a spiral channel plate, a group of
FB’ and FD’ solutions (2, 5 and 10 nM, each in quadruplicate) were tested with 3-
min spinning at room temperature. Successful hybridizations have been achieved
between the oligonucleotide samples and their complementary probe lines. As
depicted in Figure 5-3(b) inset, high specificity resulted in the alternative patterns
103
of fluorescent patches. For instance, along the radial AD probe lines, fluorescent
patches appeared only from the group of FD’ oligonucleotide samples, but not
from the oligonucleotides FB’. In each group of samples, increased
concentrations led to increased fluorescent intensities of the patches.
Figure 5-3 DNA hybridization on a CD-like glass chip. (a) The schematic diagram of hybridization patches formed at the intersections between 6 sample channels and 3 probe lines. (b) The fluorescent image of the entire glass disk. The 3 straight traces are resulted from the radial flow of the fluorescent marker during probe immobilization. The 3 grey spiral traces are resulted from the spiral flows of marker during sample hybridization. Hybridization results obtained in the rectangular region are expanded to give the middle inset. The right inset shows the groups of rectangular patches formed near the disk center, which are resulted from the hybridization of different concentrations of oligonucleotide samples with their complementary probe lines. The probe lines (AD or AB) were created by 40 min-incubation of 25-µM aminated oligonucleotide probes in the radial channels. Oligonucleotides hybridizations were achieved at room temperature in 3-min spinning at 700 rpm, and then dried out at 3600 rpm. Reprinted with permission from [129], Copyright © 2008 Elsevier Ltd.
AD
AB
AB
B’F
D’F AD
AB
AB
Rectangular hybridization patches after washing
Glass disk immobilized with probe line arrays
Samples in spiral channels flow over probe lines
(a)
(b)
10 nM B’F
The fluorescent marker line
5 nM B’F
2 nM B’F
10 nM D’F
Radial AD probe line
Radial AB probe line
5 nM D’F
104
On the same chip with the same conditions, calibration curves of both
oligonucleotide samples are shown in Figure 5-4(a). It was found that as low as
0.5 nM of FB’ or FD’ could be detected. As compared to the conventional
microarrays, in which ~ 50-µL sample is usually incubated at one time, the
microfluidic microarray method only requires as low as 1 µL of samples.
Moreover, this method does allow for the use of a flexible sampling volume to
improve sensitivity. For instance, with a 1-µL sample, the signals from 0.1 nM FB’
could not be detected effectively under the current conditions (Figure 5-4(b)).
However, by spinning the MMA five times each with 1 µL of the sample solutions,
an enough signal could be “accumulated”. It was found that the hybridization
intensity of 5 µL of 0.1-nM FB’ was comparable to that of 1 µL of 0.5 nM FB’
(Figure 5-4(b)). Therefore, the MMA method offers another way to detect the
samples with lower concentration of targets with an in-channel concentrating
step.
105
Figure 5-4 (a) The calibration graph of the hybridization signals from oligonucleotide FB’ (top curve) and FD’ (bottom curve). (b) The hybridization signals of FB’ samples using different solution concentrations and volumes. In all cases, the samples were hybridized to 25-μM probe lines at room temperature for 10 min and the error bars describe the standard deviations of the signals from 9 hybridization patches. The fluorescent intensities expressed have already been subtracted from the background. Reprinted with permission from [129], Copyright © 2008 Elsevier Ltd.
5.3.3 Hybridization of PCR products on CD-like MMA
In comparison with the oligonucleotide samples (~20 mer), the PCR
products have much longer strands (~260 bp). In this case, only a short section
(~20 bases) of the long strand can anneal to the oligonucleotide probes
immobilized on the glass surface, and the strand must align itself to be in register
with the complementary sequence of the probe. This re-annealing process
required longer time for PCR products than for the complementary
oligonucleotide samples, and the process should be promoted by higher
temperature [265]. It was found that 5-min continuous flow is not enough for the
detection of the PCR product samples (FD’P). As depicted in Figure 5-5(a), the
signal intensity from the hybridization of 20-nM FD’P with 10-min continuous flow
was less than half of the intensity from that of 5-nM FD’ conducted by 5-min
0
30
60
90
1µL of 0.5nM 1µL of 0.1nM 5µL of 0.1nM
Microfluidic operation
Flu
ores
cen
t in
ten
sity
(R
FU)
y = 53.518x + 30.584R2 = 0.9974
y = 29.52x + 41.408R2 = 0.9965
0
100
200
300
400
500
600
700
0 2 4 6 8 10Oligo sample concentration (nM)
Flu
ore
scen
ce i
nte
nsi
ty (
RFU
)
(b) (a)
106
continuous flow at 45 ºC, even though the PCR product had a 4-fold higher
concentration and took 2-fold longer hybridization time than the oligonucleotide
sample. Stop-flow method was thus applied in PCR product detections to
achieve stronger signals. The hybridization signals increased when the FD’P
samples were incubated inside the spiral channels for up to 2 hours under the
stop-flow conditions (Figure 5-5(a)).
Figure 5-5 (a) Comparison of different flow conditions for the hybridization of oligonucleotides and PCR products at 45 ºC. From left to right the hybridization conditions were: oligonucleotide samples (FD’, solid bar) by continuous flow for 5 min, PCR products (FD’P, hatched bar) by continuous flow for 10 min, or by stop-flow incubation for 10, 30, 60 and 120 min. For continuous flow, the spun rate was 500 rpm; whereas for stop-flow incubation, the samples were first introduced at a spun rate of 700 rpm for 2 min. For oligonucleotide sample, 5-nM FD’ was used because it already gave sufficiently high intensity; for PCR products, 20-nM FD’P was used, but the signal for 10-min stop-flow hybridization of FD’P was not detected and the variation of background was shown instead. The error bars describe the standard deviations of the signals from 9 hybridization patches. (b) The effects of time and temperature on the hybridization of PCR products. FD’P (20 nM) was introduced into spiral channels by spinning at 700rpm for 2min followed by incubation in an oven for different times at different temperatures. Reprinted with permission from [129], Copyright © 2008 Elsevier Ltd.
This long-time incubation also helps when the hybridizations are carried
out at higher temperatures. As shown in Figure 5-5(b), the fluorescence intensity
0
100
200
300
Flu
ores
cen
t in
ten
sity
(R
FU)
0
100
200
300
35ºC 45ºC 55ºC
Hybridization temperature
Flu
ore
scen
t in
ten
sity
(R
FU) 30min
60min 120min
Stop-flow
(a) (b)
5 min
10 min
10 min
30 min
60 min
120 min
Continuous-flow
107
increased with hybridization time and 2-hour incubation gave the highest signals
at each temperature. However, water vapour could diffuse out slowly through
PDMS [266], which may lead to unwanted sample drying inside channels during
the incubation process when the time was longer than 2 h. Therefore, the 2-hour
hybridization time was used in the subsequent work.
Figure 5-5(b) also depicted the effect of temperature on the signals. The
signal intensity at 45 ºC is higher than that obtained at 35 ºC, but it drops at 55
ºC. This result was consistent with that of the previous work [105], where FD’P
solution was incubated with its complementary probes on agarose-coated slides
at 42 ºC overnight.
5.3.4 Hybridization specificity on CD-like MMA
The hybridization specificity of both PCR products and oligonucleotide
samples to radial probe line arrays was further examined. In the conventional
DNA microarray method, in order to remove non-specific binding after overnight
incubation, a lengthy washing step with buffer solutions at different
concentrations is always needed during the post-hybridization procedure [223].
Moreover, the efficiency of washing is not always satisfactory because the
diffusion rate of the bulk solution to the glass surface is low, which might easily
cause comet-like dots to appear in the final results [19]. In contrast, the
microfluidic washing method is fast and efficient. By spinning the assembly at a
high speed for a few minutes, the sample flow continually removed any un-
hybridized DNA molecules and no further channel washing was needed. After 1-
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min of brief cleaning of the dust on the glass surface with a buffer solution, the
glass disk was ready for fluorescent scanning.
(c) D N N N N N N N B N N N N N N N D
40nM D6'PF PCR
20nM D6'PF PCR
10nM D6'F oligo
5nM D6'F oligo
Figure 5-6 The hybridization specificity shown by the plots of fluorescent intensities versus locations in the spiral channels. The samples are fluorescein-labelled oligonucleotide (FD’) and PCR products (FD’P), each at 2 concentrations. (a) The samples flow from left to right intersecting the AB and AD probe lines alternatively. (b) The samples flow from left to right intersecting various probe lines in this sequence: AD, 7 non-complementary probe lines, AB, 7 non-complementary probe lines, and AD, as depicted in the box as D, N, B, N and D, respectively. (c) The fluorescent images correspond to the hybridizations and backgrounds shown in (b). All the probe lines were created by 40 min-incubation of 25 μM aminated oligonucleotide probe. Oligonucleotide sample hybridizations were achieved by 3-min spinning and dry-out at room temperature. For PCR products, they were firstly introduced into channels by spinning and then incubated in oven at 45°C. After hybridization for 2 hours, the DNA sample solutions inside channels were spun out at 3600rpm. Reprinted with permission from [129], Copyright © 2008 Elsevier Ltd.
Figure 5-6 showed the hybridization specificity of different samples on the
glass disk. The fluorescent intensities were extracted from the spiral track of
sample flows. We have explored 2 different formats to print the probe lines. In
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Figure 5-6(a), the probes AB and AD were created in an alternative manner. The
known intersection locations between the radial probe lines and the spiral
channels help to identify the non-binding locations in order to measure the
background level. In reality, the probe creation is not conducted in this alternative
fashion. In other words, the probes do not repeat in close proximity. So in Figure
5-6b, every two AD probe lines were spaced by 15 oligonucleotide probes, which
are non-complementary to both FD’ and FD’P. The plots show high signal-to-
background ratios for the hybridizations to the two complementary probe lines
(AD) immobilized on both ends, as compared with the signals on the non-
complementary probes (AN and AB) in between. The fluorescent patches of the
data in Figure 5-6b were also shown in Figure 5-6(c), indicating the high
specificity of hybridizations achieved in the spiral microchannels.
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5.4 Conclusions
Detection of fungal pathogenic DNA has been achieved at the intersection
between the spiral sample channels and the radial probe lines created with two
independent microfluidic channels plates. Hybridizations using oligonucleotides
and PCR products were tested at different conditions such as probe
concentrations, hybridization times and temperatures. It was found that the PCR
products were detected at the level of 1 µL of 20 nM (or 3 ng) at 45 °C in 2 h;
whereas the oligonucleotides could be detected as low as 0.5 fmol (in 1 µL) at
room temperature in 3 min. The advantages offered by the intersection approach,
such as flexibility in probe line construction, low sample consumption, fast
hybridization rate and multi-sample capability, have been demonstrated on a 100
× 100 microarray because of the ease in liquid delivery offered by centrifugal
pumping. This method will facilitate the fast diagnosis of greenhouse crop
diseases because there are usually many plant samples to handle.
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6: OPTIMIZATION OF A CD-LIKE MICROFLUIDIC MICROARRAY DEVICE FOR THE FAST DISCRIMINATION OF FUNGAL PATHOGENIC DNA
6.1 Introduction
DNA microarray analysis is generally performed by passive hybridization
of samples on glass slides microspotted with probes. To reduce reagent
consumption and facilitate target diffusion to the substrate surface, microfluidics
has been integrated into the hybridization-based DNA microarray technology
[267]. One approach is to deliver one DNA target sample to the spotted probe
region enclosed within a microchamber [60, 72-74, 76, 86, 87, 106, 108], or a
serpentine microchannel [89, 90, 109]. However, these methods do not deal with
many samples simultaneously. To achieve this goal, another approach is to
deliver DNA targets via many microchannels which intersect with lines of
preprinted probes [84, 91, 93, 94, 96]. Such an approach has previously been
applied to immunoassays by Delamarche et al. and a few other groups [123,
125], and it is also very useful in parallel DNA hybridization, especially when
multiple samples are involved and a high probe density is not needed, such as in
single nucleotide polymorphism (SNP) studies [93, 94, 106]. In these reports, the
sample volume has been reduced down to 1μL, and the hybridization time was
shortened to be < 10 min, and so far up to 16 microchannels were ever used.
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Parallel hybridizations in multiple sample microchannels greatly demand
an effective way in simultaneous liquid delivery. A common method used in
microfluidics is pressure-driven pumping. However, a high pressure is required
for liquid delivery in long and narrow microchannels, and this in turn requires a
very tight sealing between the microfluidic channel plate and the substrate [90].
An alternative method is to utilize the body force of the liquid column itself, and
such a force can be created under a centrifugal force field. As compared with
other methods, centrifugal pumping is easy to implement and it can move fluids
in a parallel manner in many channels of a wide range of sizes. Even with this
advantage, however, most of centrifugal pumping applications are still limited to
the radial direction [106, 108, 129, 133, 149, 152, 153, 156, 157].
To fully utilize the centrifugal advantage, we have already developed the
microfluidic microarray method for DNA hybridizations with a microchip
consisting of 96 channels [129, 133]. Here, hybridizations occurred in the spiral
microchannels that orthogonally intersected with the radial probe lines pre-
printed on a glass disk and liquid delivery in these channels has been achieved
by centrifugal pumping. The previous work applied mainly to the fast analysis of
oligonucleotide DNA. In this work, we extend the method for the fast detection of
~260-bp PCR products. With the improvements in flow control, microchannel
design and the use of Cy5 dye labels, the detection of less than 0.2-ng PCR
product (in 1 µL) was achieved within 3-min hybridization. This is an
improvement to our previous work using fluorescein as the fluorescent labels, as
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described in Chapter 5. Moreover, fast single-base-pair discrimination of two
Botrytis species has been achieved with the improved method.
6.2 Experimental
6.2.1 Fabrication of microfluidic devices.
The fabrication of the radial and spiral PDMS channel plates has been
described in Chapter 2 and Chapter 5.
6.2.2 Oligonucelotides and the preparation of fungal pathogenic DNA samples.
The sequences of oligonucelotide probes, previously designed to detect
two greenhouse plant pathogens, Botrytis cinerea (with probe AB) and Didymella
bryoniae (with probe AD), have been listed in Table 3-1 [105]. The sequences of
the primers (Cy5-ITS2 and ITS1F) used for PCR are also shown in Table 6-1. All
oligonucleotides were synthesized and modified by Sigma-Genosys (Oakville,
ON, Canada) or International DNA Technologies (Coralville, IA).
Genomic DNAs of B. cinerea, D. bryoniae and B. squamosa were
provided by Carol Koch from Agriculture and Agri-Food Canada. The amplicons
were generated by PCR amplification of their respective genomic DNA using the
primers (ITS2 and ITS1F) specific to septate fungi, as described previously [105].
Fluorescent dyes were incorporated in PCR products through the Cy5 or
Fluorescein-labelled forward primer (Cy5-ITS2 or Fl-ITS2) during amplification.
After PCR, samples were purified with a DNA purification kit (QIAquick, Qiagen,
Mississauga, ON, Canada) to remove excess primers and nucleotides. The DNA
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concentrations of the amplicons were measured using a UV-Vis
spectrophotometer (ND-1000, NanoDrop Technologies, Montchanin, DE). The
purified amplicons were named as CB’P (264 bp), CD’P (259 bp), and CBN’P
(264bp), related to the genomic DNA of B. cinerea, D. bryoniae and B.
squamosa. The central sequences of the sense strand of CB’P and CD’P are
complementary to the sequences of the probes AB and AD, respectively. But the
binding between CBN’P and probe AB has one base-pair mismatch as compared
to that between CB’P and probe AB (i.e. TTT:ATA instead of TAT:ATA in the
center of the DNA strand).
Table 6-1 Oligonucleotide primers used in this study
Acronym Length Sequence (5'-3')
Cy5-ITS2 20-mer Cy5-GCT GCG TTC TTC ATC GAT GC
ITS1F 22-mer CTT GGT CAT TTA GAG GAA GTA A
6.2.3 Sample hybridization and fluorescent detection.
As depicted in Chapter 5, the surface of the plain glass disk was
chemically modified and preprinted with radial probe lines [129]. The PDMS
spiral channel plate was then assembled with the disk (Figure 5-2). Afterwards,
the DNA target solutions (0.5-1.0 µL, prepared in 2.5x SSC plus 0.2% SDS) were
added to the inlet reservoirs using a micropipette. In centrifugal-flow method, the
disk assembly was mounted on a rotation platform which was enclosed in a
plastic box with temperature control. By spinning, the sample solutions
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continuously flowed through the spiral channels and hybridized with the
preprinted radial probe lines. The control of the hybridization time was achieved
through adjusting residence time by using different rotation speeds (1400~3000
rpm). The flow visualization and residence-time measurement during disk
spinning were achieved with the assistance of a stroboscope light (Nova-Strobe
DA Plus, Monarch Instrument, Amherst, NH) [65, 129, 133]. In suction-flow
method, the sample solutions were filled through the microchannels by applying
a negative pressure at the outlet reservoirs. The flow rate in this method was
controlled by adjusting the pressure. As for the stop-flow method, sample
solutions stayed in the microchannels and the disk assembly was kept in an oven
at 42 ºC for 2 h.
In all cases, after hybridizations, there was no further channel washing,
but only whole-disk washing was used. This simplified the operation procedures.
First, the disk assembly was spun at 3600 rpm to dry the channels, and then the
PDMS chip was peeled off. Afterwards, the glass disk was washed briefly with 2x
SSC + 0.2% SDS (1 min.), and with 2x SSC (1 min.), and then dried in a nitrogen
stream. The glass disk was scanned on a laser fluorescent scanner to obtain the
hybridization results as previously described [129]. The excitation wavelength
was 488 nm or 633 nm for fluorescein-labelled or Cy5-labelled samples,
respectively. The photomultiplier tube (PMT) voltage was set to 600V.
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6.3 Results and discussion
6.3.1 Fast and parallel hybridization using continuous centrifugal flow.
Microfluidic DNA hybridization has fast kinetics and sensitive detection
because continuous replenishment in addition to diffusion is involved in DNA
target transport to the surface-immobilized probes. The dynamic DNA
hybridization behaviours in microchannels have been characterized in numerous
reports [84, 87, 91]. In the previous chapter, 3-ng PCR products were detected
by microfluidic hybridization only after 2-h stop-flow and at 45°C [129]. In this
work, a lower amount of PCR products (CB’P and CD’P) were detected under
two flow conditions, continuous-flow as well as stop-flow. Figure 6-1(a) shows the
hybridization results obtained from the fluorescent image of the test disk. There,
18 samples in seven groups flowed through adjacent spiral microchannels and
intersected orthogonally with 3 preprinted radial AB probe lines. Since CB’P is
complementary to the probe sequence, hybridization occurred and rectangular
patches formed at the intersection areas. On the other hand, the non-
complementary CD’P samples were not retained by immobilized probe AB and
they were washed away immediately in the continuous-flow method. No patch
was seen at the intersection areas on the image. However, in the stop-flow
method, when PCR product samples were incubated in microchannels for a
longer time (2h), non-specific binding of DNA was observed along the spiral
channels shown as strips in the image. We believe that, in the continuous-flow
method, the dynamic sample flow prevented the dye-labelled DNA targets from
accumulating and binding non-specifically onto the glass surface. For a good
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comparison of signal-to-noise ratio, Figure 6-1(b) depicted various fluorescent
intensities resulted from hybridizations in adjacent spiral channels on the bottom
radial AB probe line shown on Figure 6-1(a). For 3.2-ng PCR products, the
continuous-flow method gave fluorescent signals similar to those from the stop-
flow method, but this was achieved at the benefit of 40-fold decrease in
hybridization time. From Figure 6-1(b), it can also be seen that the background
signals from the continuous-flow method (the baseline of the first six peaks) are
much lower and more homogeneous than those from the stop-flow method
(shown as a series of small bumps). Therefore, the continuous centrifugal flow
method provided short reaction time as well as good signal-to-noise ratios for the
hybridization experiments.
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Figure 6-1 Comparison between the continuous-flow and stop-flow methods of hybridization. (a) The fluorescent images show the PCR product hybridizations conducted with two different flow methods at 42 ºC. The dark rectangular patches represent the specific binding of the complementary targets. 1.0 μL of PCR products (CB’P or CD’P) were applied to the spiral microchannels. Probe AB was used to print radial probe lines (b) Line graph showing the average fluorescent intensities along the bottom radial probe line intersected with 20 spiral sample channels depicted in (a). (c) Hybridization signal comparison of two continuous-flow methods on same microchannel plate. Here, six groups of oligo probe AB were preprinted and distributed evenly on a glass disk as shown in the inset. Sample solutions (0.2ng CB’P in 2.5xSSC+0.2%SDS), driven by either centrifugal force or vacuum suction, flowed through and intersected with these probe lines. Each bar represents signals from the average of nine hybridization patches. The bar number in the graph matches to the number as shown in the inset, indicating the position of hybridization along the spiral channels. The error bars represented the standard deviation of hybridization signals from the nine patches. The sample volume is 0.8 μL and the rotation speed or vacuum was controlled to ensure an average 3 min of hybridization time. (d) Picture of the broken liquid column (in red) inside a 24-μm depth microchannel during vacuum suction. The inset shows the magnified picture of the area. Reprinted with permission from [134], Copyright © 2010 Elsevier Ltd.
The centrifugal-driven method was also compared to the vacuum suction
method for microfluidic DNA hybridization using sample CB’P and the
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complementary probe AB. Figure 6-1(c) depicted the comparison of hybridization
signals with two flow methods. Here, it was found in vacuum suction method,
there were more signal variations among adjacent spiral microchannels and
among different positions on each spiral channel. These two variations could be
attributed to two reasons. First, due to the tiny volume of microchannels, a small
variation in the pressure applied at the outlet might cause a considerable change
in liquid flows. Second, fragmentation of sample flows at the end of the channel
was found in the vacuum suction method (Figure 6-1(d)), which resulted in the
variation of hybridization intensities at different positions (1~6 as shown in the
inset of Figure 6-1(c)) along each spiral channel. On the contrary, continuous
centrifugal flow method gave higher signals together with less signal variations.
Considering the relative small errors among repeated experiments, parallel
hybridization in multiple channels could be readily attained on the microfluidic
disk by employing the centrifugal force field.
6.3.2 Enhanced sensitivity by the control of flow, channel depth and temperature.
After confirming that the continuous centrifugal flow produced good
hybridization results, the effect of the rotation speed on hybridization signals was
carefully examined. In centrifugal force driven microflow, the disk rotation speed
affects the flow rate of the liquid inside microchannels. This determines the
residence time of sample solutions which is defined as the net time from the start
of liquid filling in the microchannel to the complete dry-out of the liquid plug. We
predicted that a lower rotation speed (or a higher residence time) would result in
120
stronger hybridization signals. As shown in Figure 6-2(a), the residence time of 1-
μL sample solution decreased from 4.3 min to 1.3 min with the increase of the
rotation speed from 1400 rpm to 2400 rpm (1400 rpm is the lowest rotation speed
below which centrifugal pumping could not be achieved in this experiment). This
corresponded to the decrease in the hybridization signals as the rotation speed
increased. Therefore, it is concluded that, in the continuous centrifugal flow state,
the lowest achievable rotation speed gave the strongest sample hybridization
signal.
Hybridization efficiency obtained in microchannels of different channel
depths was investigated. Here, we compared two depths of microchannels, 24
μm and 75 μm, in two PDMS chips. To prevent any effect resulted from the
difference in volumetric flow rate, the rotation speeds were adjusted to ensure an
equal residence time of 3 min in each case. The resulting hybridization signal-to-
noise ratios for 0.2 and 3.2-ng PCR products were shown in Figure 6-2(b). It was
found that for both high and low concentrations of DNA samples, the shallower
microchannel gave a better sensitivity. The signal-to-noise ratios from the 24-μm
microchannel chip are twice as high as those from the 75-μm microchannel chip.
The reduction of microchannel height enhanced mass transport of target DNA to
the capture probes and thus generated higher hybridization signals. Moreover,
DNA molecules could be stretched in microflows, which offered further
advantages for hybridization efficiency [84, 87, 110].
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Figure 6-2 Enhanced sensitivity due to smaller channel depth and higher temperature. (a) The bar graph showing the measured fluorescence intensities from the hybridization of 1.6-ng CB’P at different rotation speeds at room temperature. The line graph shows the corresponding residence times. The error bars were calculated from three measurements. (b) The effect of channel depth on hybridization signal intensity. Different amount of PCR products (CD’P) were hybridized at 42°C for 3 min. (c) Fluorescent intensities along an AB probe line. Ten samples (CB’P) were detected on the test disk at different concentrations and each sample was conducted in duplicate. From left to right, five samples (6.4, 3.2, 1.6, 0.8, and 0.2 ng) were first hybridized at room temperature (23°C) for 3 min. After dry-out of these channels, another group of 5 samples was hybridized at 42°C for 3 min. In all cases, the volume of sample solutions was 1.0 μL. The insets showed the magnified graphs of the hybridization signals of 0.2 ng CB’P. (d) Calibration curves of hybridization signals of PCR products (0.2~6.4 ng). The error bars represented the standard deviation of hybridization signals from six patches. Reprinted with permission from [134], Copyright © 2010 Elsevier Ltd.
The calibration curve for PCR product detection with the proposed method
was examined at room temperature and at 42°C on the same disk. Figure 6-2(c)
shows the signal variations resulted from various samples hybridized to one
radial probe line on the disk. It was found that the signals obtained at 42°C were
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more than twice as high as the signals from the room temperature experiment.
This observation matches with the conventional microarray method, which is
usually performed at higher temperature for better sensitivity [65]. Nevertheless,
with flow hybridization, room temperature test also gave both enough specificity
and low background in a 3-min period, and 0.2-ng PCR products can be
detected. The corresponding calibration graphs from 5 different sample amounts
ranged from 0.2-6.4 ng were also depicted in Figure 6-3(d), showing good
linearity for both room-temperature and 42°C flow hybridization. It is concluded
that the best hybridization is obtained with the 24-μm deep spiral channel plate,
spun at 1400rpm and maintained at 42°C.
6.3.3 Enhanced detection sensitivity due to the use of Cy5 dye labels.
In Chapter 5, we reported that 3.2-ng fluorescein labelled PCR products
(FD’P) were barely detected at 45°C after 10-min hybridization [129]. With the
improvements achieved in this work, 0.2-ng Cy5 labelled PCR products gave a
signal-to-noise ratio of 41 in 3-min flow hybridization at 42°C (Figure 6-2(c)).
Although different hybridization behaviours related to other dye labels of DNA
were discussed in many reports [268-271], no comparison has been made
between the microchip hybridization signals from DNA labelled with Cy5 and
fluorescein dye molecules. In this experiment, the relative hybridization
intensities of DNA with the above mentioned labels were examined. Here single-
strand oligonucleotides complementary to the immobilized probes were used as
targets to rule out any possible effect from the overhanging strand and possible
secondary structure of longer PCR product samples [272]. From the hybridization
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results in Figure 6-3a, it can be found that the signal-to-noise ratio of 0.1-μM FD’
is around 20 while this number for Cy5 dye labelled samples (CD’) at same
concentration is close to 1000. This phenomenon cannot be explained by
different fluorescent quantum efficiencies because this value of Cy5 dye label in
aqueous buffer is reported as ~0.2 while that of the fluorescein dye label is ~0.6
[273, 274].
To further examine if the presence of fluorescent labels may affect
hybridization efficiency, the Cy5-labelled and fluorescein-labelled samples was
mixed and applied to the microchip to study competitive hybridization. The results
were compared with the signals from solutions containing FD’ or CD’ alone. It
was found that the presence of different labelled targets showed a competitive
effect. In terms of the results scanned at the fluorescein wavelength (532nm), it
can be seen that CD’ in the mixture strongly inhibited the hybridization of FD’, to
a degree up to ~90% in comparison with pure FD’ samples. But the hybridization
signals from the mixture scanned at Cy5 wavelength (670nm) reduced only
~10% from those of pure CD’ samples (Figure 6-3(b)). The former observation
should not be caused by fluorescence resonance energy transfer (FRET)
because, while there was a large drop in the FD’ signal (scanned at 532nm),
there was no corresponding increase in the CD’ signals. The results clearly
showed that the hybridization efficiency of Cy5 dye labelled DNA is much higher
than that of fluorescein labelled DNA, and this could be explained by the strong
stabilizing effects of Cy5 on the duplex DNA [275].
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Figure 6-3 Enhanced hybridization signals of Cy5-labelled oligonucleotides due to higher hybridization efficiency and less photobleaching. (a) signal-to-noise ratio from the hybridization of different labelled oligonucleotides with the same probe lines. The results of fluorescein-labelled DNA are expanded to give the right inset picture. Here, the concentration of both oligonucleotide samples is 0.1 μM. (b) Comparison of hybridization efficiency between Cy5-labelled and fluorescein-labelled oligonucleotides. The left two bars show the normalized fluorescent intensities from the hybridization of CD’ or CD’ + FD’ (scanned at 670nm). The right two bars show the normalized fluorescent intensities from the hybridization of FD’ or CD’ + FD’ (scanned at 532 nm). In all the cases, the final concentrations of different labelled oligonucleotides are 1 µM. (c) Photobleaching effect on different dye labelled oligonucleotides. Normalized fluorescent intensity from the chip with hybridized oligos at the specific wavelength of fluorescein dye. In all the cases, 1 µL of 0.1-µM oligo samples labelled with Cy5 or fluorescein dyes were applied and hybridized at room temperature for 45min in dark place. After removal of the channel plate, the glass chip was scanned consecutively for three times and it was then exposed to room light for 4 h before it was scanned for the fourth time. The error bars here represent the standard deviations of the hybridization signals of six patches. Reprinted with permission from [134], Copyright © 2010 Elsevier Ltd.
To examine if the photobleaching effect of the fluorescein label plays a
role, repeated scans were performed on the hybridization patches, and the mean
signal intensities were plotted as percentage of the signal intensity of the first
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scan. As illustrated in Figure 6-3(c), three consecutively repeated scans showed
no noticeable bleaching effect for both Cy5 and fluorescein labelled DNA since
fluorescent hybridization patches were subjected to laser exposure for less than
15 s. However, after exposing the hybridized chips under room light for 4h, there
was differential photobleaching effect: only 5% loss in the signals of Cy5-labelled
DNA, but 31% loss of the signals of fluorescein-labelled DNA. The results
demonstrated the superior signal stability of Cy5 dye over fluorescein dye labels.
In summary, an enhanced detection sensitivity with greater hybridization signals
were obtained due to higher hybridization efficiency and less photobleaching
effect of the Cy5 dye label.
6.3.4 Discrimination of PCR products with single base-pair difference.
With the optimization in flow and channel design, the specificity of the
microfluidic method was exploited further for the discrimination between two
related Botrytis species, B. cinerea and B. squamosa. The two PCR amplicons
differ in only one base pair in the middle of the 264-bp long sequence. In this
manner, they hybridized with the probe AB to produce two types of duplexes,
namely the perfectly matched (PM) duplex from CB’P and the mismatched (MM)
duplex from CBN’P. Because the latter duplex will have a lower melting
temperature, discrimination can be achieved by applying thermal stringency to
denature MM, but not PM. This is usually performed in the classical microarray
method for single-base-pair discrimination [90, 276]. Here, the hybridization
efficiency at four hybridization temperatures was consecutively tested on the
same disk. Figure 6-4 depicted the images and signal intensities of the
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fluorescent patches resulted from the hybridization of samples in 3 spiral
channels to 3 preprinted radial probe lines. Although hybridization signals were
quite strong at 23°C, discrimination was poor. The PM signal reached a high
value at 42°C, and it was almost 2 times higher than that at 23°C (room
temperature). Thereafter, the PM signal was reduced at higher temperatures. As
for the mismatched duplexes (MM), the signal intensity kept decreasing with the
increase of hybridization temperature. The discrimination ratios between the PM
and MM duplexes, which were calculated by dividing the PM signals over the MM
signals, were plotted in Figure 6-4(b). It was found that hybridization at 62°C
gave the best differentiation with a ratio of ~14. As shown in the rightmost image
of Figure 6-4(a), the MM signals at 62°C are the lowest, and are comparable with
the background, indicating the best discrimination. Therefore, higher temperature
improves discrimination at the expense of signal intensity. In view of sufficient
hybridization intensity and good discrimination ratio, 52°C was chosen as
optimum.
127
Figure 6-4 Differentiation of Botrytis species with single-base-pair difference at various hybridization temperatures. (a) 4 groups of fluorescent images showing 9 patches of matched duplex and 9 patches of mismatched duplex. Each image was obtained from the hybridization of sample solutions in 3 spiral channels intersecting with 3 probe lines at the specified temperature. Two PCR products, perfectly matched CB’P (PM) and mismatched CBN’P (MM), were tested in the experiment. (b) Bar graphs showing the fluorescent intensities from the hybridization patches in (a). The error bars represent the standard deviations of the hybridization signals of nine patches. The connected line shows the discrimination ratio between the PM and MM species. In these discrimination experiments, 1.0-μL PCR products (1.6-ng CB’P or CBN’P) were applied in triplicate to the inlet reservoirs of 6 spiral channels Then the sample solutions flowed into the spiral channels by spun at 1500 rpm for 3 min first at 23 ºC (room temperature). After this operation, the channels were dried out at 3600 rpm and the temperature of the assembly was raised to 42 ºC. Then another batch of sample solutions was applied to another 6 spiral channels on the same chip and the process was repeated. The procedure was repeated similarly for hybridization at 52 ºC and 62 ºC. Reprinted with permission from [134], Copyright © 2010 Elsevier Ltd.
0
1000
2000
3000
4000
5000
6000
23ºC 42ºC 52ºC 62ºC
Hybridization temperature
Sig
nal
in
ten
isty
(R
FU
)
0
3
6
9
12
15
Dis
crim
inat
ion
rat
io
PM
MM
Ratio
(a) (b)
23ºC 42ºC 52ºC 62ºC
PM MM PM MM PM MM PM MM
128
6.4 Conclusion
A microfluidic CD-like chip with spiral microchannels was further studied
for the detection of pathogen PCR samples. The centrifugal pumping method
used in this paper showed advantages over vacuum suction flows in parallel
solution delivery and signal variations between duplicated samples. The sample
residence time in the microchannel was predictable at a certain rotation speed.
The effect of microchannel depth was studied and enhanced sensitivity was
achieved with the use of shallower spiral channel plate (24-μm depth). Cy5 dye
labels were proved to show much higher hybridization efficiency as well as less
photobleaching effect, as compared with the fluorescein dye labels used in the
previous work. The calibration curves of PCR product detection at two
temperatures were constructed with a sample load from 0.2 to 6.4ng (in 1 μL).
With optimized conditions, the discrimination between two 260-bp PCR products
with one base-pair difference was achieved in duration as short as 3 min. The
microfluidic chip has the capacity to analyze up to 100 samples per chip
simultaneously.
129
7: ANALYSIS AND MODELING OF FLOW IN ROTATING SPIRAL MICROCHANNELS: TOWARDS MATH-AIDED DESIGN OF MICROFLUIDIC SYSTEMS USING CENTRIFUGAL PUMPING
* Section 7.3 and Appendix A were written based on the work of Dr.
Kropinski from the Department of Mathematics with the aid of my
experimental data.
7.1 Introduction
Centrifugal pumping has been demonstrated to be a convenient liquid-
driven method in microfluidic applications [180]. Unlike pressure-driven or
electrokinetic techniques, the method avoids the use of tubing or electrical
connections, and parallel sample transport can be easily achieved. Centrifugal
pumping has been successfully applied to immunoassays [156, 160, 277], multi-
ion analysis [149], protein crystallization screening [278], DNA hybridization [106,
108, 133], as well as blood separation and analysis [155, 159, 163]. By using
different microstructure designs, liquid flow and mixing can be controlled in
rotating microchannels. Recent microfluidic applications integrated with
centrifugal pumping method were summarized in many reviews [147, 148, 279,
280]. Although the approximate equations for flow rate estimation have been
given in these reports, more rigorous flow dynamics studies have been pursued
130
for the better understanding of liquid flows in rotating radial microchannels [136,
169, 171, 173-177, 281]. For example, analytical solutions were proposed for
centrifugal-force-driven filling flows in either circular or rectangular microchannels
[136, 173-175]. With commercial CFD tools, numerical solutions have also been
proposed and have been compared to experimental data [171, 176, 177].
Currently, almost all of the fluidic channel patterns used for centrifugal-
pumping microflow are designed in the radial orientation. This radial design has
several limitations: (i) the dimension of fluidic structure in radial direction is
restricted. The centrifugal microfluidic platform usually aims to fit the well-
developed compact disk (CD) system to utilize the signal reading and rotor
driven/control system [145-148, 282]. If a disk of standard CD size (120 mm in
diameter) is used, the maximal dimension in radial direction is ~5 cm. Therefore,
the applicable space is limited considering that no reversed flow design is
allowed in centrifugal pumping method. (ii) The centrifugal force increases with
the increase of radius. As characterized in the work of Duffy et al. [156], for a
liquid flowing into an empty radial channel from a reservoir, the average velocity
of the flow (U) is given by:
2 2
32Hd r rU Lρω
µ∆=
where the determinants include fluid properties (ρ: density; μ: viscosity),
the rotation rate (ω: angular velocity), configuration of the channels (dH: hydraulic
diameter; L: channel length), and the location of the liquid column ( r is the
average distance from the liquid column to the rotation center, and Δr is the
131
radial extent of the liquid column subject to centrifugal force). Therefore, the
average velocity of the liquid is not only related to the rotation speed, but is also
affected by the further extension of the liquid column in a microchannel. Such an
increasing flow velocity puts forward challenges and difficulties in the design of
fluidic structure especially near the rim of a disk. (iii) At last, when extra
pressures such as capillary pressure exists, it is hard to get a balanced flow for
both spatial and temporal control of flow with radially-distributed patterns. The
capillary effect is an important factor during the liquid flow process in short and
narrow channels [283, 284]. In many practical applications, microchannels are
made from polymeric materials such as polydimethylsiloxane (PDMS) or
polymethylmethacrylate (PMMA). The contact angle of water on these polymers
can be more than 90°, which generates a capillary barrier pressure (Pcb) at the
liquid front for aqueous based solutions. On the other hand, the centrifugal
pressure acting on the liquid in radial channels is given by [147]:
2mP r rρω= ∆
Liquid flow will not be initiated unless the pressure at the meniscus of
liquid front (Pm) is larger than the capillary barrier pressure (Pcb). Once the
rotation speed (ω) reaches the critical point, the liquid plug in microchannels
starts to move forward. However, with the advancing of the liquid front, Δr
increases and so does Pm. The balance between centrifugal driven force and
capillary barrier is then broken and the flow speed starts varying. A flow pumping
force which is not related to the length of the radial extent is thus needed.
132
In our previous work, we have designed an equiforce spiral microchannel
on a CD-like microchip and a constant centrifugal force component was
produced along the microchannel [133, 285]. Parallel transport and detection of
nucleic acid samples was performed for 3 min in spiral microchannels under the
centrifugal force [129, 133, 134]. From experimental observations, it was found
that the liquid flow driven by the centrifugal force in spiral microchannels was not
affected by the radial extent of the liquid front. The flow velocity is mainly
determined by the rotation speed of the disk assembly. In this work, we carried
out a detailed study of centrifugal-driven flows inside the equiforce spiral
microchannels. The experimental measurement of the microflow at different
rotation rates was performed by analyzing the digital-video recording of the liquid
flow. Then, the Navier-Stokes equations of incompressible flow were rewritten in
a new orthogonal curvilinear-coordinate system based on the spiral design. An
approximate analytical solution to the Navier-stokes equations was deduced and
fitted to the experimental data. In addition, we investigated the centrifugal flow
behaviours in spiral microchannels by carrying out three-dimensional numerical
simulations. The results were compared to the experimental observations and
the mathematical modeling solutions.
133
7.2 Chip design, microfabrication and flow measurement of the spiral microchannels
The layout of the spiral channel has been reported in previous chapters.
The fabrication of the PDMS channel plates was based on the soft
photolithography technique which has been reported in Chapter 2 [94, 129]. The
surface profile of the microchannels was obtained by using a profilometer
(Alphastep 500, Tencor Instruments, Mountain View, CA) and the measured
channel height and width are 33 μm and 90 μm, respectively.
The liquid flow in the spiral channels was visualized using aqueous
solutions colored with food dye. As shown in Figure 7-1a, a piece of white paper
preprinted with position lines was put underneath the glass disk, which was used
as a background for easy observation of the liquid front movement. The flow
visualization during disk spinning was achieved with the assistance of a digital
video recorder and a stroboscope light (Nova-Strobe DA Plus, Monarch
Instrument, Amherst, NH). The displacement of the front of the colored liquid
column can be measured by calculating the number of lines passed on the paper
background (Figure 7-1b). Time data were extracted from each frame of the
movie which was recorded at 30 frames per second.
Contact angles of solutions on the microchip surfaces were measured with
an OCA 15 Plus contact angle microscope (Dataphysics Instruments GmbH,
Filderstadt, Germany). The liquid drop images were taken with a charge coupled
device (CCD) camera. The liquid drop shape was snapped from the images to
134
infer the contact angles with suitable software (SCA 20 from Dataphysics
Instruments GmbH).
Figure 7-1 (a) The photograph of the equiforce spiral channel assembly before spinning. One inlet reservoir was filled with colored solutions and a piece of paper printed with grey position lines was placed underneath to facilitate the measurement of the liquid front position. (b) Magnified picture in (a) shows the image of inlet reservoirs and a microchannel partially-filled with red dye solution. Reproduced from [286] by permission of The Royal Society of Chemistry.
7.3 The mathematical model
The layout of the equiforce spiral channel has been reported in previous
work [285]. The spiral curve was designed so that the angle α between the radial
direction and the tangent (see Figure 7-2a) satisfies the following equation
cosr kα = (1)
where k is defined as the degree of spirality ( cosk r α= ) and it is a
constant. The value of k is determined by the inlet and outlet positions of the
spiral channel. In our case, the microchannel is confined within a 92-mm
diameter plate and the beginning and the end of the spiral curve are set to be 21
1cm
(a) (b)
135
mm and 42 mm from the center of the plate, respectively. Therefore, the value of
k equals to 3.32 mm for a 200-mm long spiral channel, which is calculated by the
initial r value of 21 mm and initial α value of 80.9001°. This k value is the same
for the final r of 42 mm and final α of 85.4644°. This geometry ensures that the
along-channel component of the centrifugal acceleration is constant.
The motion of an incompressible fluid in a centrifugally driven flow is
governed by the Navier-Stokes equations. Written in a frame of reference
rotating with the disk, these equations are:
21( ) ( ) 2 pt
νρ
∂+ ⋅∇ +Ω× Ω× + Ω× = − ∇ + ∇
∂u u u R u u (2)
together with the continuity equation
0∇⋅ =u (3)
for the fluid velocity u, time t and the pressure p. The constants ρ and ν
are the fluid density and kinematic viscosity, respectively. In this frame of
reference, the boundary conditions for the fluid velocity are the usual “no-slip”
boundary conditions. The term Ω × (Ω × R) is the centrifugal acceleration at
angular velocity Ω = ωk, R is the position within the channel, and 2Ω × u is the
Coriolis term.
In order to obtain a mathematically tractable physical model, we proceed
under the following assumptions:
1) The Coriolis force 2Ω×u is assumed negligible in comparison to
the centrifugal force.
136
2) Any surface tension effects are neglected.
3) The external pressure differences between the inlet and the outlet
boundaries are assumed to be zero.
4) The liquid front is advanced under a quasi-steady approximation;
i.e. / 0t∂ ∂ =u .
5) The flow is unidirectional and it is only along the s direction.
6) The microchannel has a short, radial “neck” which joins the inlet
reservoir to the entrance of the spiral channel. This neck region is
assumed to play a negligible role in the fluid motion within the spiral
portion of the channel. The role of this region will be investigated in
future studies.
Ducrée et al. carefully investigate assumptions 1 and 2, and determine
that these assumptions are valid for moderate rotation speeds [177]. Considering
that both the inlet and outlet reservoirs are open to air, assumption 3 is
reasonable, and this assumption has also been used in the work from other
groups [174, 177]. In terms of assumption 4, it is valid in the case of thin-film
flow, [287] and Kim et al. have further proved its validity for the flow in a rotating
rectangular microchannel [174]. The assumption 5 assumes that the transversal
channel flow, un and uz are negligible compared to the down-channel flow us and
they are thus equal to 0. The assumption 5 has been verified through numerical
simulation by CFD program as shown in Appendix B.
137
Before proceeding with the reduction of the Navier-Stokes equations
under the above assumptions, we introduce a right-handed orthogonal curvilinear
coordinate system (n, s, z), with unit vectors en, es, and k, respectively, that are
aligned with the spiral portion of the microchannel (Figure 7-2). The s-coordinate
measures the distance along the spiral, where s = 0 corresponds to the start of
the spiral, and s = l(t) is the position of the liquid front, n is the across-channel
distance, 0 ≤ n ≤ W, and z the channel height, 0 ≤ z ≤ H. Details of this
coordinate system and the reformulation of the Navier-Stokes equations for a
fluid velocity u = unen + uses +uzk and pressure p(n, s, z) are given in Appendix
A.
Figure 7-2 (a) The layout of the equiforce spiral channel and the orthogonal curvilinear coordinate system used for the mathematical modeling of the liquid flow inside the spiral microchannel. (b) 3-D magnified view of the spiral microchannel in the curvilinear coordinate system. H and W are channel height and width, respectively. Reproduced from [286] by permission of The Royal Society of Chemistry.
Under the assumption of a unidirectional flow only along the s direction, un
= uz = 0, which has been validated in narrow channels by the CFD simulation
(a) (b)
138
(Results shown in Appendix B), the the s-momentum Navier-Stokes equation
reduces to (Details can be found in Appendix A):
( )2 1,Ts
pk u n zs
ω νρ∂
− ∆ = −∂
. (4)
where the operator ΔT is,
2 2
2 2T
n z∂ ∂
∆ = +∂ ∂
,
Integrating equation (4) with respect to s gives
( ) [ ]20
1, ( , )Tsk u n z s p n s Pω ν
ρ − ∆ = − − ,
where P0 is the pressure at the inlet of the spiral channel. Neglecting any
external pressure difference between the inlet and the outlet implies
that ( )( ) 0, p l t n P= , and the only way this is satisfied is to require that
( ) 2, , 0 , 0Tsu n z k n W z Hν ω∆ = < < < < , (5)
which we solve together with the no-slip boundary conditions
( ) ( ) ( ) ( )0, , 0, , 0 , 0.s s s su z u W z u n u n H= = = = (6)
A global mass conservation argument determines that the velocity of the
liquid front must be equal to the average of us across the channel. Thus,
( )0 0
1 , H W
sdl u n z dndzdt WH
= ∫ ∫ (7)
139
Before solving equation (7), we seek the solution to (5) satisfying
boundary conditions (6) in the form of an eigenfunction expansion. This yields
( )2
21,3,5, 1,3,5,
16 1, sin sinsp q pq
k p qu n z n zpq W H
ω π ππ ν λ
∞ ∞
= =
=
∑ ∑
. (8)
where
2 2
pqp qW Hπ πλ = +
.
Substituting (8) into (7) and integrating yields
2
4 2 21,3,5, 1,3,5,
64 1 p q pq
dl kdt p q
ωπ ν λ
∞ ∞
= =
= ∑ ∑
. (9)
This equation provides the relation to construct the plot of the liquid
meniscus displacement (l) versus time (t) in order to fit the experimental data.
7.4 Numerical simulation of the microflow
Numerical simulations of the centrifugal filling flow in the spiral
microchannel were studied using an ESI-CFD package (Advanced CFD 2009,
ESI North America, Bloomfield Hills, MI). The dimensions and the geometry of
the 3-D models are shown in Figure 7-3. The geometry was generated from the
spiral pattern used in the microfabrication of the PDMS microchannels. The
channel cross-section is 90 μm (width) × 33 μm (depth), which were measured
from experimental observations. The 3-D geometry was computationally
discretized into structured quadratic elements as shown in Figure 7-3(b) and (c).
A grid with 35, 970 cells was used in the transient flow simulations. Here, the
140
model of the microchannel is comprised of three parts: an inlet reservoir of 1-mm
diameter, 2-mm long straight neck channel from the inlet, and the 200-mm long
spiral channel. The inlet starts at a distance of 19 mm from the center of rotation.
The simulations were run on a Dell T7400 workstation with 4 GB of RAM and
Intel Xeon processors; each simulation typically required ~1 week of computer
execution time. Details on the governing equations, parameter settings, and
simulation procedures are given in Appendix B.
Figure 7-3 (a) A bird’s-eye view of the 3D geometry of the equiforce spiral microchannel used in CFD simulations. (b) Magnified view of the inlet region with a tilted inlet reservoir and a neck channel. Point A denotes the starting position of the spiral channel where the neck channel connects. (c) Magnified view shows the structured grid of the microchannel near point A. The cell widths range from 15 µm to 75 µm. The grid lines are as close to 90° as possible and small cell aspect ratios were employed to ensure a good modeling quality. Reproduced from [286] by permission of The Royal Society of Chemistry.
Neck
Spiral
Inlet (a) (b)
(c)
Inlet
A
A
O
Disk center
141
7.5 Results and discussions
7.5.1 Characterization of microflows in equiforce spiral channels with experimental data
Liquid flows inside the rotating spiral channels were imaged by using a
stroboscope imaging system. Figure 7-4 depicts the images of the movement of
the liquid column inside a spiral microchannel. From Figure 7-4 (a) to (c), three
snapshot images of the disk in motion were captured, showing that the liquid
front moved from the 11th line then passing the 15th line to the 22nd line under
centrifugal force. From these images, the displacement of the liquid front was
measured, and the data was plotted versus time (Figure 7-4 (d) to (f)). The data
was obtained from three of the spiral channels in the same disk rotating at 1500
rpm. It was found that the filling flow is steady through the whole 200-mm
channel with a constant slope under a certain rotation speed. This is unlike the
centrifugal-pumping flow in radial microchannels, where the flow speed also
depends on the radial distance between the liquid front and the rotation center.
With our spiral microchannel design, the radial length of the liquid column has
negligible effect on the overall flow speed. The flow speed, which could be
deduced from the slope of the displacement curves, was found to be 5.10 ± 0.03
mm/s. For comparison, the average flow speed in a radial microchannel with
similar dimension and rotation speed was calculated to be ~44 mm/s [147].
The start length of the liquid front during measurement is not zero. This is
because it takes a couple of seconds for the disk to be accelerated from the
stationary state to reach the set rotation speed in our system and the liquid has
flowed into the microchannels for a few millimeters before a stable strobescopic
142
image can be obtained for analysis. Moreover, pipette pressure at inlets during
the sample loading procedure varies and the start length could be very different
for different measurements even at same rotation speed. In Figure 7-4 (d) to (f),
although the start lengths are 7.8 mm, 9.3 mm, and 12.6 mm, respectively, the
liquid front velocities are 5.1 mm/s in all cases. The coefficient of variation of the
experimental flow velocities measured from three microchannels is less than 1%.
For comparison, flow data from measuring the moving liquid rear was also
shown in Figure 7-4 (d) to (f). In our experiment, the total volume of a 90μm (W)
×33μm (H) ×200mm (L) microchannel is 0.5 μL. After a solution of this amount
fills through the microchannel, the inlet reservoir starts emptying out under the
centrifugal force. To test any change in flow speed during liquid filling and
emptying processes, the distance of the receding liquid rear was also measured
with the similar method and was depicted in the figures. From the linear fit of the
displacement-to-time graph it is concluded that the liquid receding flow is also
steady. Moreover, by comparing liquid filling and emptying curves, we see that
the two slopes are similar to each other and the coefficient of variation in
calculated flow rates is less than 10%. Therefore, the speed of liquid filling
process can represent steady flow in our spiral microchannels.
143
Figure 7-4 Liquid movement inside microchannels. (a), (b) and (c) show the 3 snapshot images of the disk spun at 1500 rpm, where 1 and 2 designate the 10th and 20th position lines, respectively. The black arrows denote the inlet reservoirs and the white arrows indicate the liquid front. The spiral trace extended as time increased, indicating the movement of the liquid front along the microchannels. (d), (e) and (f) represent the displacement-to-time plots showing the movement of both the liquid front and liquid rear meniscus in 3 adjacent spiral channels. The start lengths of the liquid front measurement are 7.8 mm, 9.3 mm, and 12.6 mm, respectively. Reproduced from [286] by permission of The Royal Society of Chemistry.
7.5.2 Comparison of solutions from the mathematical model with the experimental data.
The mathematical model was validated with the experimental data. By
using the measured parameters, equation (9) was plotted as a distance (l) vs.
time (t) curve. The comparison between the mathematical modeling solutions
and experimental data of liquid front movement at 6 different rotation speeds are
depicted in Figure 7-5(a). A fairly good agreement between approximate
theoretical model predictions and the experimental findings was observed at
rotation speeds ranging from 1400 to 2400 rpm. It is revealed that the deviations
0
40
80
120
160
200
0 20 40 60 80 100
Men
iscu
s di
spla
cem
ent
(mm
)
Time (seconds)
0
40
80
120
160
200
0 20 40 60 80 100
Men
iscu
s di
spla
cem
ent
(mm
)
Time (seconds)
0
40
80
120
160
200
0 20 40 60 80 100
Men
iscu
s di
spla
cem
ent
(mm
)
Time (seconds)
(a) (b) (c)
(d) (e) (f) Liquid front
Liquid rear
Liquid front
Liquid rear
Liquid front
Liquid rear
144
between the experimental and mathematical results appear to be very small at
lower rotation speeds. However, at higher rotation speeds, the velocity of liquid
front was slightly faster than that predicted by the mathematical model.
The mathematical model has also been used to evaluate the effect of the
variation in channel width and depths on the liquid flow behaviour. Currently,
microfluidic devices are usually fabricated using photolithograph techniques [193]
and the uniformity of microchannel width could be limited by many factors, such
as photomask resolution and the wavelength of UV light used in
photolithography. Figure 7-5(b) shows microscope images of two PDMS
microchannel plates. It can be seen that the channel shape varies and the width
deviation is as high as 10 % in the channel plate. In addition, depending on the
quality of the spin-coating and subsequent channel-developing processes, the
depth of microchannels also fluctuates. With the aid of the mathematical model,
the effect of the variation of channel dimensions on the centrifugal-driven flow
inside equiforce spiral channels is shown in Figure 7-5c. With a 10% variation in
channel width, the flow speed only changed by less than 3%. In contrast, the
variation of channel depth has much more influence on the flow. Up to a 16%
increase of flow speed was found with a 10% deeper channels.
The proposed model could help in the design of microchips with
equiforce microchannels. For instance, if a chip with a different spiral pattern is to
be designed, the mathematical model could offer a quick and accurate prediction
on the flow behaviour. We use this model to examine the flow behaviour of 2
different equiforce microchannel patterns used in our work (Figure 7-5(d)) [65].
145
Although a narrower microchannel (25 μm in height and 50 μm in width) was
used, the larger k value counteracted the effect of the narrow geometry, and the
liquid front velocity was in fact higher than that of wider and deeper channels.
Figure 7-5 (a) Liquid front displacement versus time at different rotation speeds. Data points represent experimental data and the solid lines are theoretical curves plotted using the mathematical model (The curves and data points were displaced horizontally for clarity). (b) Microscope images of 3 channels in a PDMS chip showing the width variation. The scale bar represents 100 μm. (c) Calculated variation of flow velocity as affected by the variations in channel width and depth using the proposed mathematical model. (d) Liquid front displacement versus time graph from two spiral-microchannel chips of different channel geometries. Data points represent experimental data and the solid lines are from the model prediction. Here, W, H, and U are channel width, channel height, and measured liquid-front velocity, respectively. Both microchips were rotated at 1500rpm. Reproduced from [286] by permission of The Royal Society of Chemistry.
-20%
-15%
-10%
-5%
0%
5%
10%
15%
20%
-10% -5% 0% 5% 10%
Dimensional variations
Flow
spe
ed v
aria
tions
Channel widthChannel depth
020406080
100120140160180200
1400 rpm 1500 rpm 1600 rpm 1800 rpm 2000 rpm 2400 rpm
Liqu
id fr
ont (
mm
)
Time (Sec)
0
20
40
60
80
100
Time (Sec)
Liqu
id fr
ont (
mm
)
(a) (b)
(c)
10 sec 100 µm
5 sec
k = 3.3 mm k = 7.0 mm Math model
W: 50 μm H: 25 μm U: 6.8 mm/s
W: 90 μm H: 33 μm U: 5.1 mm/s
(d)
146
7.5.3 Validation of the assumptions in the mathematical modeling with the experimental data and simulation results
During the mathematical modeling, we employed 5 assumptions to
simplify the Navier-Stokes equations. Although the model shows reasonable
agreement with experimental data, further studies were performed to examine
the validity of these assumptions. Due to instrumental limitations, the resolution
of time could not be finer than 0.4 sec and the liquid front displacement could not
be measured accurately for a difference within 1.5mm. Moreover, the pressure
inside the microchannels could not be measured. Therefore, numerical studies
with commercial CFD program were used to visualize the transient flow filling
process during the initial stage. Glatzel et al. evaluated the performance of four
commercial programs for different microfluidic applications including centrifugal
microflows [171]. The authors recommended ESI-CFD for the simulation of free
surface flows involving capillary forces [171]. We adopted to use this program
which has also been used by many groups in the numerical studies of steady or
transient microflows with validation from experimental data [176, 177, 284].
7.5.3.1 The quasi-steady state approximation
In this paper we present a quasi-steady state approach for mathematical
modeling the flow-pattern. Here, it is assumed that u does not depend on time.
From the linear fit of the liquid front advancing curves in Figure 7-5(a), it is
already observed that the flow is steady during liquid filling through the 200-mm
spiral channel. Numerical studies were performed to find out how long it will take
for the transient filling flow to reach such a steady state. With the CFD program,
transient filling processes during the first 1.5 seconds were simulated. Here, the
147
inlet reservoir was prefilled with 0.5-μL liquid as what we usually did during the
experiments (Figure 7-6(a)). Because liquid in the reservoir usually crawled into
the spiral channel due to the pipette loading pressure, a small part of the
microchannel was also filled with liquid column as initial conditions in the
simulation (Figure 7-6(a)). This is the start length of the liquid column which
varies in different simulation studies to mimic the real experiments.
The simulation results of the speed of the liquid front at corresponding
times were collected and plotted in Figure 7-6b. It is found that the transient filling
speeds are high at the beginning. The shorter is the start length, the higher is the
initial flow speed. However, the liquid front movement quickly slows down and
reaches a quasi-steady state, shown as the flat part in Figure 7-6(b). This
situation can be considered as a steady flow because the flow velocity variation
is small. As shown in Figure 7-6(c), the flow velocities at 1.5 seconds differ from
each other by less than 5%. Moreover, these flow speed values are very close to
the experimental data run at the same rotation speed (Figure 7-6(c)). Therefore,
the quasi-steady state approximation in our mathematical modeling is reasonable
and valid except during initial stage, which is highly transient. The different start
length of liquid column in the spiral microchannels has a negligible effect on the
filling flow speed during most of the time.
148
Figure 7-6 (a) Image showing the initial conditions used for transient flow simulation. The blue color represents the part of the channel filled with air and the pink color denotes liquid solutions. (b) Simulated liquid front displacement versus time at 1500 rpm with different start lengths. (c) comparison of the liquid front velocities at 1500 rpm with experimental data, mathematical modeling, simulation of transient filling flow and simulation of steady flow. Reproduced from [286] by permission of The Royal Society of Chemistry.
7.5.3.2 The approximation of the negligible Coriolis force.
The Coriolis force is a fictitious force in a non-inertial rotation reference
frame. Since the force is perpendicular to the flow direction, it has been utilized to
induce secondary flows at high rotation speeds for applications in flow switching
or passive mixing [136, 172, 177]. In the mathematical model, the motion of an
incompressible fluid in a centrifugally driven flow is governed by the Navier-
Stokes equations under a rotation reference frame. The Coriolis term is
neglected to simplify analytical solutions, and this approximation has been used
0
2
4
6
8
10
12
14
0 0.3 0.6 0.9 1.2 1.5
Time (sec)
Liq
uid
fro
nt
velo
city
(m
m/
s)
0 mm5 mm7.8 mm9.3 mm12.6 mm
(a) (b)
Start length
Neck length
0
2
4
6
8
Experimentdata
Mathmodeling
Transientflow
simulation
Steady flowsimulation
Liqu
id fr
ont v
eloc
ity (m
m/s
)
(c)
149
by many mathematical studies on the flow velocity in radial microchannels at a
lower rotation speed [136, 173, 177].
To examine the effect of the Coriolis force on the flow in equiforce spiral
channels, both experimental data and simulation results were collected at two
rotation directions, anti-clockwise and clockwise directions. As the sign symbol of
the Coriolis force term in equation (1) depends on the direction of rotation, the
difference between the flow velocities under two different conditions should be
notable if the secondary flow induced by the Coriolis force is not negligible. Here,
a high rotation speed, 2400rpm, was used throughout the experiments and
simulations to demonstrate the possible effect of Coriolis force. The results were
shown in Figure 7-7. From the experimental data in Figure 7-7(a), it is found that
the rotation direction showed negligible effect on flow velocities; the liquid front
velocities at two rotation directions differ from each other by less than 2% (Figure
7-7(a) inset). The evaluation of the Coriolis effect with simulation results was
shown in Figure 7-7(b). Since the start length of the liquid column was set to be
same value as found in experimental observations, the unsteady part of the liquid
front velocity is very short and less than 0.1 s. Furthermore, the liquid front
velocities (in mm/s) at the quasi-steady state for both direction 11.3 ± 0.5, 11.2 ±
0.7, respectively, which are not significantly different. The results support the
assumption of the negligible Coriolis effect in our mathematical model.
150
Figure 7-7 (a) Liquid front displacement versus time from experimental data at 2400 rpm. The inset shows the liquid front velocities from fitting the experimental data in both cases. Because a longer acceleration time was required to achieve a higher rotation speed, the start length is much longer, which is around 50 mm. (b) Simulated results of the liquid front velocities at 2400 rpm from anti-clockwise and clockwise directions. Reproduced from [286] by permission of The Royal Society of Chemistry.
7.5.3.3 Scaling the effect of the surface tension force.
The effect of surface tension force on microflows has been studied
extensively [283, 284, 288-290]. In rectangular microchannels, the surface
tension force per unit mass can be deduced from the Young-Laplace equation
and is written as [177, 289]:
2 cos 1 1ss
PFl l W H
γ θ = = +
.
where Ps is the pressure from surface tension force at liquid front, l is the
length of the liquid column, γ is the surface tension of the liquid, θ is the contact
angle, W and H denote the width and depth of the channel, respectively. On the
other hand, because the centrifugal force in this work has been designed to be a
constant along the spiral microchannel, we thus obtain:
15 20 25 30 35 40 45 50 55 6040
80
120
160
200
Anti-clockwise Clockwise
Liqu
id fr
ont (
mm
)
Time (Sec)
(a) (b)
0.0 0.1 0.2 0.3 0.4 0.5 0.6
0.000
0.004
0.008
0.012
0.016
0.020 Anti-clockwise Clockwise
Velo
city
(m/s
)
Time (Sec)
0
4
8
12
16
20
Anti-clockwise
Clockwise
Liqu
id fr
ont v
eloc
ity (m
m/s
)
151
2F kω ρω= .
where k is a constant and is defined in equation (1). The effect of the
surface tension force could be evaluated using a dimensionless ratio of the
centrifugal force (Fω) to the surface tension force (Fs):
( )2
2 coss
F lWHF W Hω ρω γ
γ θ=
+.
The ratio turns out to depend on ω, l and θ. Figure 7-8(a) shows the graph
of Fω and Fs versus different liquid column length and contact angles at a rotation
speed of 1500 rpm. The centrifugal force is constant along the spiral
microchannel and it is shown as a flat plane in the graph. However, the effect of
the surface tension force on the liquid flow is associated with both the length of
the liquid column and the contact angle. As seen in the plot, the surface tension
force is comparable to the centrifugal force only during the initial filling stage, but
not when the liquid column develops more into the spiral channel. A more
dominant factor is the contact angle of the liquid. When the solid surface is
hydrophobic and the contact angle is close to 90°, Fs can be completely
neglected. In our experiments, the solid substrate is either PDMS polymer or
chemically-treated glass with an organic layer on top, the contact angles of the
solutions on these substrates were usually found to range from 40° to 80°.
Therefore, surface tension force can only take effect during the very short initial
stage, which is highly transient. Figure 7-8(b) shows the CFD simulation results
predicting the difference in liquid front velocities at this stage for two different
solutions. The contact angles of solution A and B on the substrate were 60° and
152
46°, respectively. The liquid front velocity of solution A is 30% slower than
solution B during the first 1.5 s. On the other hand, we did not observe a
significant slower liquid front velocity from our experimental results using these 2
solutions (results not shown). The discrepancy could be attributed to the
phenomenon of the dynamic contact angles during liquid movement [173]. Figure
7-8(c) shows the measured contact angles of the two solutions on the PDMS
surface. The difference in static contact angles are around 15°. However, when
liquids are advancing, both contact angles increase and the difference in
dynamic contact angles is less than 5°. Therefore, if a solution with lower surface
tension coefficient and a hydrophobic substrate such as PDMS or modified glass
were used, which are common in the bio-application of microchips, neglecting the
surface tension force will not introduce a significant error. Moreover, because
surface tension is independent of rotation speed, this effect can also be
incorporated into the Navier-Stokes equations as a constant pressure term
added onto the liquid front in our future modified mathematical model [291].
153
Figure 7-8 (a) Comparison of the centrifugal force (Fω, shown as a gray plane.) and the surface tension force (Fs, shown as a color surface) along the microchannel at 1500 rpm (b) Simulated the liquid front velocities at 1500 rpm from two solutions (A and B) with different contact angles on the solid substrate (c) Measured dynamic contact angle change of the two solutions from experimental observations. Reproduced from [286] by permission of The Royal Society of Chemistry.
7.5.3.4 The effect of the neck channel
As seen in Figure 7-6(a), the microchannel has a short “neck” channel
which joins the inlet reservoir to the starting point of the spiral channel. The
average length of the neck channel is 2 mm. In our mathematical model, this
neck region is assumed to play a negligible role in the fluid motion within the
spiral portion of the channel. From the comparison of the results from modeling
and experiments (Figure 7-9(a)), the predicted liquid front velocity from the
analytical solution at 2400 rpm is around 30% less than that from experimental
0.000
0.002
0.004
0.006
0.008
0.010
0.012
0.014
0 0.3 0.6 0.9 1.2 1.5
Time (Seconds)
Liqu
id fr
ont v
eloc
ity (m
/s)
Contact angle = 60 degreeContact angle = 46 degree
40
45
50
55
60
65
70
75
80
0 50 100 150 200 250 300
Run number
Con
tact
ang
le (º
)
Solution 1 on PDMS
Solution 2 on PDMS
(a) (b)
050
100150
200 2040
6080
1000
2
4
6
8
10
12
x 104
Forc
e (P
a/m
)
Liquid length (mm) Contact angle ( )
(c)
Solution B
Solution A
154
observation. We speculate that the error can be attributed to the underestimation
of the pressure induced by the neck section. The external pressure differences
between the inlet and the outlet are zero because both boundaries are open to
air and the hydraulic pressure from the reservoir solution is negligible. However,
the mathematical modeling solution was solved starting from the beginning of the
spiral channel instead of the inlet reservoir. The rotation of the short liquid plug at
the neck channel under centrifugal field does create an extra pressure on the
flow inside the spiral channels. This pressure, which could be estimated using
the equation given in the work of Madou et al. [147], is proportional to the square
of the angular velocities (Figure 7-9(b)). At a high rotation speed such as 2400
rpm, this extra pressure is around 3 times of the pressure induced at 1400 rpm.
Therefore, a significant deviation between the analytical solution and
experimental data were observed at higher rotation speeds. Further improvement
in the mathematical model is expected to include this effect.
Figure 7-9 (a) Liquid front moving velocity under different rotation speeds. Both data from experimental data and from mathematical model prediction are shown. The error bars are from the measurement of 3 adjacent channels. (b) Pressure at the beginning of the spiral channels generated from the short liquid column in the neck section under different rotation speeds. Reproduced from [286] by permission of The Royal Society of Chemistry.
0
500
1000
1500
2000
2500
3000
3500
1200 1400 1600 1800 2000 2200 2400
Rotation speed (rpm)
Pres
sure
from
nec
k (P
a)
0
4
8
12
16
20
1400 1500 1600 1800 2000 2400
Rotation speed (rpm)
Liqu
id fr
ont v
eloc
ity (m
m/s
) Experimental measurmentsMathematical modeling
(a) (b)
155
7.6 Conclusions
This work describes the experimental measurement and mathematical
modeling of centrifugal-pumping flow in spiral microchannels. Quasi-steady flow
in rotating channels has been attained on a microfluidic glass disk with the
equiforce spiral channel design. The flow velocities and residence time of
solutions can be controlled by adjusting rotation speeds. In contrast to radial
channel design, liquid flow in the spiral microchannels is more manipulatable and
the residence time of the liquid is much extended. For example, at 1400rpm, the
centrifugally driven flow in the spiral microchannels is only at a speed of 4.3
mm/s. However, the average flow speed in a radial microchannel with similar
dimension could be up to ~45 mm/s, depending on the radial extent of the liquid
front from the inlet. Because many applications of microfluidics were focused on
reactions inside microchannels, a longer residence time is required and a much
slower flow speed is favourable. The spiral design has shown good spatial and
temporal control over the position of fluids in microscopic channels, which is an
advantage when longer reaction time is important in bio-analysis applications
done in a flow system. With the employment of centrifugal pumping force, parallel
analysis for multiple samples has been achieved in our previous work.
The mathematical modeling studies in this paper were based on solving
the Navier-Stokes equations in a customized orthogonal curvilinear-coordinate
system aligned with the channel geometry. Under proper assumptions, the liquid
flow speeds predicted by the mathematical model and by the CFD program
showed reasonable agreement with the experimental measurements at different
156
rotation rates. Moreover, the assumptions used in the mathematical model have
been examined with both experimental and computational simulation data. The
mathematical model gave a flexible and rather accurate analytical solution using
much less computing power. Compared with the commercial CFD program,
where results can only be obtained in weeks for one group of parameters, the
proposed mathematical studies gave an analytical solution with similar accuracy
in seconds. The proposed study demonstrated the effectiveness of the spiral
microchannel design in microfluidic applications using centrifugal force. With
modifications, this work could be adapted to the simulation and modeling of other
centrifugal-pumping microflow systems.
157
7.7 Appendix A: The spiral coordinate system
In order to obtain the coordinates of the equiforce spiral curve, we first
consider an infinitesimal segment dθ (Figure 7-10), from which we see that
tandrdrθ α= (10)
Figure 7-10 Section of the spiral curve and the infinitesimal segment used for the calculation. Here the black solid curve is the spiral curve and the blue dashed lines are radial lines from the disk center. r and θ are the usual polar coordinates. Reproduced from [286] by permission of The Royal Society of Chemistry.
Differentiating (1) with respect to α and substituting the result into (10)
yields
2tanddθ αα= ,
which after integrating gives θ = tan α − α. We can now view the polar
coordinates along the spiral curve as being parameterized by α,
( ) ( ) ( ) [ ]0 1 sec , tan , ,r kα α θ α α α α α α= = − ∈ . (11)
θ
dθ
dr
rdθ α
The spiral curve
O
158
where the interval [ ]0 1,α α satisfies ( ) ( )1 0 2θ α θ α π− = .
To obtain the distance along the spiral, s, we observe from Figure 7-10
that cosdr ds α= . Substituting this into (11) gives
ds rdr k
=
and integrating yields
2 20
1 ( )2
s r rk
= − . (12)
We now consider a three-dimensional spiral channel of width W and
height H and whose inner wall is described parametrically through (11). We
introduce an orthogonal curvilinear coordinate system, (n, s, z), that is aligned
with this geometry. Here, s is the distance along the spiral, 0 ≤ s ≤ L, n is the
cross-channel distance, 0 ≤ n ≤ W, and z is the height above the plate, 0 ≤ z ≤ H.
Let en, es, k be a right-handed system of unit vectors in the n, s, and z directions,
respectively. The unit vectors en and es are related to the unit vectors in polar
coordinates, er and eθ through the following:
cos sinα α= +s rθe e e , sin cosn α α= −rθe e e (13)
To rewrite the Navier-Stokes equations in spiral coordinates, we must first
know the position vector R to a point described by (n, s, z) in the channel. A
straightforward geometric argument gives
cos ( sin ) nr n r zα α= + + +sR e e k . (14)
159
In addition, we must determine the scale factors, or the rate of change of
arc length with respect to each coordinate direction. The scale factor in the s
direction is
1h ns
κ∂= = +
∂R
, 1
sinrκ
α= , (15)
where κ is the curvature. In both the n and z direction, the scale factors
have unit value. Following the methodology presented in Davis and Snider [292]
for general orthogonal curvilinear coordinate systems, we determine that the
gradient and the Laplacian operators are
1= nh s n z∂ ∂ ∂
∇ + +∂ ∂ ∂se e k ,
2
2
1 1 1( ) ( )hh s h s h n n z∂ ∂ ∂ ∂ ∂
∆ = + +∂ ∂ ∂ ∂ ∂
,
For a vector field s n n zu u u= + +su e e k , we reformulate the Navier-Stokes
equations (2) in terms of the spiral coordinate system as follows:
22
2 2
1 12 ( )s ns s n n s s n
s
u upu u u u k u u ut h h s h h s h s h
κ κ κ κω ω νρ
∂ ∂∂ ∂+ ⋅∇ − − + = − + ∆ − − − ∂ ∂ ∂ ∂
u , (16)
2 22 2
1 1 12 ( ) ( )n sn s s n n s
u upu u u n u u ut h n h s h h s h
κ κ κ κω ω νκ ρ
∂ ∂∂ ∂ + ⋅∇ + + − − = − + ∆ + − + ∂ ∂ ∂ ∂ u , (17)
1zz z
u pu ut z
νρ
∂ ∂+ ⋅∇ = − + ∆
∂ ∂u , (18)
1 ( ) 0s zn
u uh huh s n z∂ ∂∂
+ + =∂ ∂ ∂
, (19)
160
where
sn z
u u uh s n z
∂ ∂ ∂⋅∇ = + +
∂ ∂ ∂u .
We now proceed under the assumption of a unidirectional flow only along
the s direction, un = uz = 0. The continuity equation reduces to
0sus
∂=
∂,
which implies that us = us (n, z). Then only the s-momentum equation (16)
is used, and the equation reduces to
2 22
2 2
1 1( )s ss
u u pk h uh n n z h h s
κω νρ
∂ ∂∂ ∂− + − = − ∂ ∂ ∂ ∂ .
(20)
The scale factor in the s direction, h = 1 + nκ, is expected to have a value
close to 1 for since n (0 ≤ n ≤ W) is much smaller than 1. Furthermore, since we
expect the cross-channel gradients to be significant, given the confines of a small
cross-sectional area, we can further simplify the above by noting that
2 22
2 2s s
su u un z
κ∂ ∂+
∂ ∂ .
Introducing the operator ΔT,
2 2
2 2T
n z∂ ∂
∆ = +∂ ∂ ,
equation (20) becomes
( )2 1,Ts
pk u n zs
ω νρ∂
− ∆ = −∂
. (4)
161
7.8 Appendix B: Simulation set-up and the study on the transversal flow with the CFD program
7.8.1 Governing equations
The transient, three-dimensional numerical simulations of the centrifugal
flow in spiral microchannels were performed based on the flow module and free
surface module of the CFD program. In the flow module, we solve momentum
equation and continuity equation under a rotation reference frames. The flow is
considered to be laminar, incompressible, Newtonian and isothermal with velocity
field u governed by the Navier–Stokes and continuity equations, and surface
tension force (Fs) at the air/liquid interface is incorporated as an additional term in
the equations used in simulations.
In the free surface module, the volume of fluid (VOF) method was used to
model the location of the fluid front during filling of the microchannel [293]. The
system consists of two incompressible and immiscible fluids represented as the
liquid and gas phases, respectively. The VOF distribution has been determined
by solving a separate passive transport equation, given as
0f ft
∂+ ⋅∇ =
∂u
where f is the volume of fluids function (f = 1 in grids completely filled with
water, f = 0 in grids filled with air, and f has a fractional value corresponding to
the volume fraction of water in partially filled grids).
162
7.8.2 Volume, boundary, and initial conditions in the numerical simulations
Since both the inlet and outlet reservoirs were open to air without any
extra fluidic connections, the boundary conditions of inlet and outlet were set to a
fixed pressure of 0 Pa. This pressure condition is the same as that used in
literature reporting the simulation of the flow in a radial microchannel [171]. All
the walls were taken to be non-compliant (or rigid) and were defined as rotating
walls with the same angular velocity as the global frame of reference. The wall
boundary conditions used for the simulations involve no-slip condition with
contact angles at the front specified for each wall (to be consistent with the
experimental conditions, as obtained from the contact angle measurements of
the microchannel materials). The contact angle of the fluid with the bottom wall
(chemically-modified glass surface) is 52.8° ± 2.1°. The top and side walls of the
microchannel are PDMS, and the contact angle is 73.2° ± 2.5°.
During our experiments, the inlet reservoirs were filled with 0.5~1.0 μL of
solution before the chip assembly was spun. To match the experimental
conditions, we started the simulation with initial conditions that assumed 0.5 μL of
liquid present in the inlet reservoir. Moreover, because the liquid could crawl into
the microchannel under the pressure from the pipetting process, we also
assumed a certain start length of liquid column in the microchannel as initial
conditions.
The fluids under consideration are the buffer solution as the liquid, and air
as the gas. The thermo-physical properties of the solution were measured and
163
applied directly in the computational simulations. For air and the buffer solution
respectively (at room temperature), the densities are 1.614 kg·m-3 and 1020
kg·m-3, respectively, and the dynamic viscosity (µ) are 1.846 × 10-5 kg·m-1·s-1 and
1.25 × 10-3 kg·m-1·s-1, respectively. Because of the addition of surfactant in the
buffer solution, the surface tension of the air-liquid interface was measured at
0.03 N·m-1, a value smaller than that for pure water.
In the simulations, the uniform rotation speed was imposed at a steady-
state value in either clockwise or anti-clockwise direction to match the
experiments. The center of the rotation axis corresponded to the center of the CD
and was located at a distance 21 mm from the start of the spiral channel.
The computational model included the flow module to solve the fluid
dynamics field as well as the free surface module to model the advancing of the
liquid front during microchannel filling. This transient process was solved using an
unsteady solver with implicit first-order Euler time integration under rotation
reference frames (i.e., centrifugal microfluidics). Simulations were performed in
automatic time steps with a scale around 1 × 10-5 s. The air/liquid interface was
reconstructed using a second order piecewise linear interface calculation. Explicit
formulations were used and each time step was calculated via the Courant-
Friedrichs-Lewy parameter (set to 0.1), which restricts the size of the time step to
ensure the free surface did not cross an entire element within that time step.
164
7.8.3 The effect of mesh grid density on the computation time and accuracy during the numerical simulations
Two different resolutions were used in the CFD simulation of the system.
A structured grid with 35, 970 cells was used in the transient flow simulations and
the cell numbers at the cross section are 5×2 cells. In steady-flow simulation, the
whole microchannel was filled with solution and a grid of much higher density
was used. The total computational cells are 1,834,560 with a symmetry plane
and the cell numbers at the cross section are 20×12 cells. Because the channel
was initially filled with air, the free-surface module in CFD-ACE program was
used to solve the surface-reconstruction procedures. To keep the run times
within reasonable limits, the number of cells was simplified resulting in a much
lower grid density.
To examine if the mesh density in transient-flow simulation is sufficient for
the calculation of the liquid front velocity, we compared the results from steady-
flow simulations using two resolutions. With low-density mesh, the cross-channel
resolution is 5 × 2 cells (Figure 7-11a(i)). With high-density mesh, the cross-
channel resolution of the computational grid is 20×12 cells (Figure 7-11b(i)). It
can be seen in Figure 7-11a(ii) and b(ii) that the predicted down-channel flow
velocities (us) are similar from these two meshes. Table 7-1 also lists the
maximum down-channel flow velocities (us_max) calculated from both grid
settings. The us_max calculated under 5 × 2 grids is only 0.4% in difference from
that calculated under 20×12 high density grids. The results indicated that the
low-density mesh is sufficient in predicting the liquid front position, which is
determined by the down-channel flow velocities. On the other hand, the 5 × 2
165
grids did not give accurate distribution on transversal cross-channel flows (un and
uz, as shown in Figure 7-11a(iii) and b(iii)) and the maximum values (un_max and
uz_max) calculated from both mesh settings are very different from each other
(Table 7-1). Because the purpose of the transient filling-flow simulation study is
to accurately predict the position of the advancing liquid column in a rotating
microchannel, accurate calculation of down-channel flow velocity (us) is more
important than the calculation of cross-channel transversal flows (un and uz).
Table 7-1 Comparison of the simulation results from two different mesh densities.*
us_max (mm/s)
un_max (mm/s)
uz_max (mm/s)
CPU time of each cycle
(Sec)
Low-density mesh 24.5 0.030 3.5×10-5 178
High-density mesh 24.6 0.043 0.012 2928
* Because the purpose of the transient filling-flow simulation study is to accurately predict the position of the advancing liquid column in a rotating microchannel, accurate calculation of down-channel flow velocity (us) is more important than the calculation of cross-channel transversal flows (un and uz).
The low-density mesh saved a lot of computation time. As seen in Table
7-1, for steady-flow simulation, the total computation time of one cycle for the
model with low-resolution grids is less than 3 min, compared with almost 1h for
the simulation of the high-resolution grids. Considering that it usually took ~5,000
to 10, 000 cycles during our simulation practice, the use of the low-resolution
grids reflects a compromise between overall accuracy and computational effort in
the simulation of multi-phase problems.
166
Figure 7-11 Comparison of the simulation results using two meshes with different resolutions. (a) low-density mesh, cross-channel resolution is same as that used in the manuscript (5 × 2 cells). (b) high-density mode, the cross-channel resolution of the computational grid is 20×12 cells. (i) computational grids showing the cross-section of the microchannel. (ii) the color map of the down-channel flow velocities (us) at the cross-section of the microchannel.(iii) the color map of the transversal flow velocities (un) at the cross-section of the microchannel. The center black lines in high-resolution grid results are the symmetry plane.
7.8.4 Validation of the assumption of negligible cross-channel flows.
The cross-channel secondary flows are also estimated by simulation.
Figure 7-12(b) shows the flow vector map combining un and and uz in a cross-
section of the spiral microchannel as shown in Figure 7-12(a). Figure 7-12(c) to
(e) show the color maps of flow speeds in 3 directions. The maximal us, and un
are found at 24, and 0.045 mm/s, respectively. Therefore, the values of
secondary flow velocity un are less than 0.2% of that in down-channel direction.
In terms of another cross-section flow uz, it is even smaller and is calculated at
0.012 mm/s. therefore, the computed un and uz are “small” in some significant
(a) (b) (i)
(ii)
(iii)
(i)
(ii)
(iii)
mm/s
167
sense relative to the down-channel flow us. We believe that the assumption 5 in
the body text of un = uz = 0 is valid.
Figure 7-12 (a) Schematic diagram showing the position of the cross-section part of the microchannels used for secondary flow analysis. (b) The flow vector map combining un and uz. (c) The color map of us on the cross section. (d) The color map of un on the cross section. (e) The color map of uz on the cross section. The center black lines in (b) to (e) are the symmetry plane used during simulation.
(a) (c)
(d)
(e) (b)
mm/s
168
8: MODELING OF MICROFLUIDIC DNA MICROARRAY HYBRIDIZATION AND ITS APPLICATIONS TO EXPERIMENTAL OPTIMIZATION
8.1 Introduction
Like other biosensor technologies, DNA Microarray is based on the
fundamental property of nucleic acid strands specifically binding (hybridizing) to
their complementary strands [294]. Generally, probe DNA molecules are
immobilized on a solid surface and form an array of microspots. Then, labeled
target DNA strands in solution phase are applied to the surface. Because the
immobilized probe DNA binds to its complementary strand, detection is achieved
through the read-out of the tagged markers on the retained target molecules.
The conventional microarray method occurs in a static mode, where
sample DNA in bulk solutions are transported to the reactive surface solely
through molecular diffusion. This slow process could limit the rate of the
hybridization assay, leading to long-term incubation (12-18 h) and poor detection
efficiency [19]. The recent microfluidic technology enhances the mass transport
by introducing convection to the microarray system [84, 91]. Moreover, the
microfluidic method shows the advantages of less sample usage (down to
submicrolitre) and reduced assay time (in minutes) compared to the bulk solution
method [129].
169
The kinetics of DNA microarray hybridization, which is heterogeneous, is
much more complex than that observed in homogeneous liquid-phase DNA
hybridization [10, 295]. Additional parameters from mass transport mechanism,
such as bulk and surface diffusivity, flow velocity, channel geometries, etc. are
involved. A sound and detailed mathematical modeling of the ongoing diffusion
and reaction processes is thus needed to properly design both convection- and
diffusion-driven DNA microarray systems. Because the system shares many
common features with other biosensors, the theoretical studies on these
heterogeneous interactions have provided considerable insight into the process
of DNA surface hybridization. For example, a simplified two-compartment model
was originally proposed for the antigen-antibody reaction in protein biosensors
[296-301] and it was then used to analyze the on-chip DNA hybridization [302,
303]. Another diffusion-reaction model proposed by Chan et al. was developed
from a cell receptor-ligand model [304] and it has been regarded as a pioneering
work on static microarray hybridization [305, 306]. In his work, hybridizations of
targets from bulk phase and from initial non-specific surface adsorption were
considered and the model has successfully predicted the enhanced kinetics from
sparse probe coverage. Other models have also been reported to further
describe the effect of different physico-chemical parameters on kinetics during
static hybridization [57, 307, 308]. Regarding the recent microfluidic technology,
Erickson et al. coupled Chan’s work with convection transport relations and they
examined their model with experimental results from oligonucleotide targets
[309]. Similar models have been reported for other microfluidic-based surface
170
biosensors [310-312]. Because the mathematical description of these models
involves the use of nonlinear partial differential equations (PDE), numerical
solutions have been achieved with the increasing computing power of modern
computers [303, 309, 311-313].
The present work aims at providing a comprehensive analysis of the
combined effect that the many different process variables have on DNA
microarray hybridization in diffusion- and convection-driven systems. The use of
dimensionless parameters and variables in our work brings in a universal
character to the model, transforming a specific situation into a generic case, as it
has been applied in a few studies on static hybridization [314, 315].The proposed
model was solved numerically and the results have been used to predict the
calibration range of oligonucleotide targets, and to examine the effect of flow
rate, channel depth and probe coverage on hybridization kinetics. Furthermore,
the problems about hybridization spot morphology and signal variation from spots
to spots are also explained for the first time with the present model. With the
validation from experimental data, our work could provide a quick route for the
experimentalist to estimate the importance of different parameters in a
microfluidic microarray chip and thus convenient criteria which can be used in the
design process.
171
8.2 Experimental
The fabrications of the microchip used and the subsequent microfluidic
hybridization analysis have been depicted in the previous chapters.
8.3 Model construction for microfluidic DNA microarray hybridization
8.3.1 Navier-Stokes and continuity equations
The configuration of a PDMS plate with a rectangular microchannel is
shown in Figure 8-1(a) and the liquid inside the channel is assumed to flow at a
steady state in the absence of body forces like gravity. Incompressible Navier-
Stokes equations (2) are used along with the continuity equation (1) to find the
velocity profile throughout the domain.
0∇⋅ =u (1)
21 p νρ
⋅∇ = − ∇ + ∇u u u (2)
In this equation, u is the velocity vector, p is the pressure, ρ is the density,
and ν is the kinematic viscosity of the solution. Equation (2) can be further
simplified based on the thin-film flow theory, which studies the steady flow of
viscous liquid between two rigid boundaries with small distance apart [316-318].
For a typical microfluidic flow in our experiments, the height scale of the flow (H ~
30 µm) is much smaller than the length scale of the flow (L > 30 mm). Moreover,
considering that the typical flow speed (U) of the microfluidic flow is around 1
172
mm/s, the inertial term ( ⋅∇u u ) in equation (2) can be ignored because
2
Re 1HL
<<
. Therefore, the Navier-Stokes equation is reduced to:
20 p µ= −∇ + ∇ u (3)
where µ is the dynamic viscosity of the solution.
The pressure-driven, steady-state laminar flow in long and rigid channels
is also known as Hagen-Poiseuille flow [319]. The transversal flow velocities in y
and z direction are small and negligible. In microfluidics, the aspect ratio of a
rectangular channel can often be large and the channel is well approximated by
an infinite parallel-plate configuration. We thus could drop out the y coordinate
and use 2-D geometry as shown in Figure 8-1(b).
173
Figure 8-1 (a) The configuration of a PDMS plate with a rectangular microchannel filled with solutions. The bottom wall of the microchannel is immobilized with 3 probe strips. (b) The schematic diagram showing the simplified 2-D geometry of the above microchannel used for later numerical simulation. The two diagrams are not drawn to scale.
A simplified format of the equation (3) for the 2-D channel is then
expected:
2
2
1u dpz dxµ∂
= −∂
(4)
With no-slip boundary condition, the solution of equation (4) is a simple
parabola
1 ( )2
dpu H z zdxµ
= − − (5)
(a)
Outlet
Bulk solution of target DNA
Inlet
Probe regions Spacing
Bottom wall
Upper wall
H
(b)
PDMS channel plate
Microchannel filled with solutions
3 immobilized probe strips on the
glass substrate
z
x
174
If the average flow velocity (U) is defined as volumetric flow rate divided
by the cross-section area [319], then
2
12H dpU
dxµ= − (6)
and the 2-D flow velocity equation (5) becomes:
6 1z zu UH H = −
(7)
8.3.2 Mass transport and hybridization kinetics
In DNA microarray hybridization, target DNA molecules are dissolved in
bulk solution and then applied to the chip immobilized with probe arrays. As
shown in Figure 8-2, the target DNA molecule moves from bulk solution to glass
surface and hybridizes with the immobilized probe DNA. Therefore, many studies
have been based on modelling target mass transport from the bulk solution to the
reactive surfaces [311, 312, 320]. In addition to this bulk-to-surface interaction,
Chan et al. also proposed another mechanism regarding the heterogeneous
hybridization of solution-phase DNA [305, 309]. Here, target DNA molecules
adsorb non-specifically to the glass substrate first [321, 322]. Then the absorbed
target molecules could move along the surface and hybridize with the probe DNA
in a two-dimensional manner. Our model incorporates the transport of target
molecules in solution phase, the direct bulk-to-surface hybridization kinetics, non-
specific binding of target to bottom wall, as well as the subsequent surface-to-
surface hybridization kinetics.
175
Figure 8-2 (a) Schematic representation of proposed heterogeneous DNA hybridization model. The probe DNA molecules are shown as blue wave-like ribbons in the center region of the glass substrate. The target DNA molecule is a red twisted ribbon with a red pellet at one end which represents the fluorescence label. The hybridized DNA are shown as duplexes in the probe region. (b) The three kinetic processes used in the later model construction regarding the heterogeneous hybridization of target DNA: k3 and k-3 represent bulk-to-surface hybridization and dessociation of targets to the bulk phase; k2 and k-2 represent surface-to-surface hybridization and dissociation of the nonspecifically adsorbed targets; and ka and kd represent the reversible nonspecific adsorption and desorption of the targets to the surface.
Region of immobilized probe arrays
Labelled target DNA in bulk solution
Glass substrate
Hybridized DNA duplex on probe site
Non-specifically adsorbed target DNA
Bulk solution
(a)
(b) 3
3
a
d
k
k
k
k
−
Target DNA (in bulk phase) + Probe DNA (immbolized) Hybridized Duplex
Target DNA (in bulk phase) Target DNA (adsorbed on the surface)
Target DNA (adsorbed on the surface) + Prob 2
2
k
k−
e DNA (immbolized) Hybridized Duplex
176
8.3.2.1 Mass transport through diffusion and convection in bulk solution
The target DNA molecules are carried by the microflow and transported to
the reactive surfaces through convection and diffusion. Therefore, the process
can be described by the convection–diffusion equation [323]:
( )2C D C Ct
∂= ∇ − ⋅∇
∂u (8)
Where C is the target concentration in the bulk solution, and D is the
diffusion coefficient of the target DNA molecules in bulk phase. In the 2-D
microchannel model shown in Figure 8-1(b), lateral flow velocity in z direction is
small and negligible. The transient two-dimensional mass transport equation can
be rewritten as follows:
2 2
2 2
C C C CD ut x z x
∂ ∂ ∂ ∂= + − ∂ ∂ ∂ ∂
(9)
8.3.2.2 Surface hybridization and adsorption kinetics
Considering the two mechanisms of the hybridization of target DNA
molecules with the surface-immobilized probes, the formation rate of the
hybridized duplexes at the probe region is the sum of two hybridization rates as
shown in follows:
bhy shyR Rt
∂Θ= +
∂ (10)
where Θ is the surface concentration of the hybridized duplexes, Rbhy is
the hybridization rate of the target DNA from bulk phase, and Rshy is the
hybridization rate of the target DNA non-specifically adsorbed on the glass
177
surface. We assumed that the upper PDMS wall is inert and does not adsorb
DNA molecules. Because the hybridization capacity at a probe site is limited by
the total number of immobilized probes, the maximal surface concentration of
hybridized duplexes is equal to the probe density ( 0Θ ) and ( )0Θ −Θ is the
concentration of the available probe molecules on the surface. Therefore, the
bulk-to-surface hybridization rate Rbhy can be analyzed according to Langmuir
kinetics [324]:
( )3 0 3bhy wR k C k−= Θ −Θ − Θ (11)
where Cw is the concentration of the target DNA molecules adjacent to the
wall, k3 and k-3 are the hybridization and denaturation rate constant of the bulk-to-
surface hybridization process, respectively.
Similarly, the hybridization rate of the adsorbed target DNA molecules is
given as:
( )2 0 2shyR k kη −= Θ −Θ − Θ (12)
where η is the surface concentration of non-specifically adsorbed target
DNA molecules, k2 and k-2 are the hybridization and denaturation rate constant of
the surface-to-surface hybridization process, respectively. Substitute equation
(11) and (12) to equation (10), we get:
( ) ( )3 0 3 2 0 2wk C k k kt
η− −
∂Θ= Θ −Θ − Θ + Θ −Θ − Θ ∂
(13)
In order to compute the rate of change of the surface concentration of
non-specifically adsorbed target DNA ( tη∂ ∂ ), we consider the processes
178
including non-specific adsorption, diffusion along surface, and subsequent
hybridization. Therefore, the reaction-diffusion equation for the adsorbed
molecules is given as [325]:
2s ads shyD R R
tη η∂= ∇ + −
∂ (14)
where Ds is the surface diffusion coefficient of the target DNA on the glass
surface and Rads is the rate of adsorption. If we define ηmax as the maximal
adsorbable number of the target DNA at a unit area of the glass surface, Rads can
be written as
( )maxads a w dR k C kη η η= − − (15)
where ka and kd are the adsorption and desorption rate constant of the
target DNA molecules, respectively.
Substitute equation (12) and (15) to equation (14), we get:
( ) ( )2max 2 0 2s a w dD k C k k k
tη η η η η η −
∂= ∇ + − − − Θ −Θ − Θ ∂
(16)
The equation (9), (13), and (16) are coupled by a flux balance at the wall
( 0zJ = ):
( ) ( )
0 0
max 3 0 3
( , )( , , )
wz z ads bhy
a w d w
C x tC x z tJ D R Rz t
k C k k C kη η η
= =
−
∂∂= − = − = +
∂ ∂
= − − + Θ −Θ − Θ
(17)
179
8.3.3 Non-dimensionalization of the reaction-diffusion and kinetic equations.
Non-dimensionalization is a useful tool in simplifying physical systems
[315, 317]. It rescales the parameters and variables so that all computed
quantities are of relatively similar magnitude. The units in the system are also
wiped out. In the governing equations shown in the last section, the different
variables such as time (t), channel length (x), channel height (z), down-channel
flow velocity (u) and bulk concentration (C) are divided by their respective
characteristic values (measured experimentally). The resulted dimensionless
forms are given as follows:
*2
ttH D
= , *2
xxUH D
= , * zzH
= , * uuU
= , *
0
CCC
= (18)
where 2H D is the diffusion timescale for a DNA molecule to travel from
channel top to channel bottom and it has been used as the characteristic time
scale, U is the average liquid flow velocity in microchannels and it can be
measured experimentally, and C0 is the initial bulk concentration of the target
DNA molecules.
With the characteristic values of flow velocity and channel height, the
dimensionless form of the 2-D flow velocity in equation (7) becomes:
* * *6 (1 )u z z= − (19)
and the transient 2-D mass transport equation (9) is rewritten as:
* 2 * 2 * **
* 2 * 2 * 2 *
1( ) ( )
C C C Cut Pe x z x
∂ ∂ ∂ ∂= + −
∂ ∂ ∂ ∂ (20)
180
where Pe is the Péclet number of the flow and it is defined as UHPe D= .
Similarly, for the reaction-diffusion equation (16) of the surface
adsorption/hybridization procedures, the dimensionless variables are
*
max
ηηη
= , *
0
ΘΘ =
Θ, *
0
ww
CCC
= (21)
Then the non-dimensionalization form of equation (16) becomes:
( )
( )
* 2 ** * *0 max
* 2 * 2max 0
* * *0 2 max 2
max 2 max
1 1( )
1
s a dw
a
s
s
D C H k H kCt D Pe x D k C
D k H kD D H k
ηη η η ηη
η ηη η
−
∂ ∂= + ⋅ − − ∂ ∂
Θ− ⋅ ⋅ −Θ − Θ
(22)
Introduce surface/bulk diffusivity ratio (φ ), relative surface capacities (ε1,
ε2, and ε3), two Damköhler numbers (Da1 and Da2) and two dimensionless
equilibrium constants ( 'D
K and '2K ), as shown
sDD
φ = , 01
max
C Hεη
= , 02
max
εηΘ
= , max1
ak HDaDη
= , 2 max2
s
k HDaD Hη
= , '
0D
d
a
kKk C
= ,
' 22
2 max
kKk η
−= (23)
Thus the equation (16) becomes
( ) ( )* 2 *
* * ' * * * ' *1 1 2 2 2* 2 * 2 1 1
( ) w DDa C K Da Kt Pe xη φ η ε η η φε η∂ ∂ = + − − − −Θ − Θ ∂ ∂
(24)
Similarly, for the bulk-to-surface hybridization kinetics shown in the
equation (13):
181
( ) ( )*
* * * * * *0 3 0 3 2 max 2*
0 3 0 2 max
1 1sw
s
C H k H k D k H kCt D k C D D H k
η ηη
− − Θ∂Θ= ⋅ −Θ − Θ + ⋅ −Θ − Θ ∂ Θ
(25)
Introduce relative hybridization capacity (ε3), Damkohler number (Da3) and
the dimensionless equilibrium constant ( '3K ),
03
0
C Hε =Θ
, 3 03
k HDaDΘ
= , ' 3 33
0 3 0
K kKC k C
−= = (26)
Then the dimensionless form of equation (13) is shown as:
( ) ( )*
* * ' * * * ' *3 3 3 2 2* 1 1wDa C K Da K
tε φ η∂Θ = −Θ − Θ + −Θ − Θ ∂
(27)
For the flux balance, the dimensionless form of equation (17) is shown as:
( ) ( )* * *
* * ' * * * ' *0 1 3 3*
( , , ) 1 1z w D wC x z Da C K Da C K
zτ η η=
∂ − = − − + −Θ − Θ ∂ (28)
The equation (19), (20), (24), (27), and (28) are used in the later numerical
simulation works.
8.3.4 Physical interpretation of the dimensionless numbers:
Five main dimensionless parameters have been introduced in the non-
dimensionalization process and they are Pe, φ , ε, Da, and K'.
The Péclet number (Pe) is a fundamental dimensionless number in
convective transport in both macroscale and microscale flow [314]. If we rewrite
its definition as follows
2 / Characteristic diffusion time/ Characteristic convection time
UH H DPeD H U
= = = (29)
182
it can be seen clearly that the Péclet number is the ratio between the
characteristic diffusion time ( 2 /H D ) and the characteristic convection time
( /H U ). Typically, flow-through and microfluidics-based assays are characterized
by high Péclet numbers (Pe >> 1), such that the convective transport dominates
over diffusion and localized depletion around probe areas is eliminated.
Considering that the flow speed is typically around 1mm/s and channel height is
30 µm in our microfluidic chips, Pe number is calculated to be ~ 200 for 21-mer
oligonucleotide targets. Therefore, microfluidics-based DNA hybridization
alleviates the limitation from diffusion, and hybridization is controlled mostly by
the reaction rate of the surface hybridization.
Biomolecules can be adsorbed to a variety of solid surfaces and these
molecules could diffuse along the surfaces [306]. During DNA microarray
hybridization, the adsorbed target molecules in the no-probe-covered regions can
diffuse to probe regions and contribute to the surface hybridization process. We
use the dimensionless number φ to calculate the ratio between the surface
diffusion coefficient (Ds) and the bulk diffusion coefficient (D) of the DNA. The
higher is the value of φ , the faster is the movement of the non-specifically
adsorbed target molecules.
The relative surface capacities consist of 3 dimensionless numbers (ε1, ε2,
and ε3). For any unit area of glass surface inside a microchannel, ε1 corresponds
to the ratio of the maximal amount of target DNA in the bulk solution ( 0C H ) to the
surface adsorption capacity of the targets ( maxη ) at that area. ε2 is a measure of
183
surface hybridization capacity relative to the surface adsorption capacity. Similar
to ε1, ε3 is the ratio of the maximal amount of target DNA in the bulk solution
( 0C H ) to the surface hybridization capacity of the targets at the unit area ( 0Θ ).
Small values of ε1 and ε3 indicate a high relative surface-capturing capacity
leading to strong depletion and a longer saturation time. On the other hand, small
ε2 indicate that the solid surface will consume too much analytes by non-specific
adsorption and pre-hybridization coatings such as using salmon sperm DNA or
bovine serum albumin is needed to prevent target depletion from non-specific
binding [19].
Damköhler number (Da) is a dimensionless number and it has been used
by many groups to relate reaction timescale to mass transport timescale of a
microfluidic system [307, 311, 312, 315, 324, 326]. In this work, three Damköhler
numbers (Da1, Da2, and Da3) are defined: Da1 is the ratio of surface adsorption
rate to the bulk diffusive mass transport rate of target molecules; Da2 is the ratio
of surface-to-surface hybridization rate to the surface diffusive mass transport
rate of target molecules; Da3 is the ratio of bulk-to-surface hybridization rate to
the bulk diffusive mass transport rate of target molecules. In a static
hybridization, when Da >> 1, the transport to the surface is strongly diffusion-
limited, while at Da << 1, the transport becomes reaction-limited at the surface
and a flat (constant) concentration profile can be expected across the channel.
Three dimensionless equilibrium dissociation constants (KD', K2', and K3'.)
are also introduced during the non-dimensionalization procedures. They have
been used as measures of the thermodynamic stability of the adsorbed targets
184
(KD') or hybridized duplexes (K2', and K3') [326]. In terms of the microfluidic DNA
microarray analysis, the smaller values of these parameters indicate higher
stability of the adsorbed targets or the hybridized duplexes.
8.4 Simulation of microfluidic DNA microarray hybridization
8.4.1 Numerical simulation with COMSOL program
Numerical simulations and visualization were performed with COMSOL
Multiphysics 3.5a. The considered domain is assumed to be infinitely wide and to
have a height (H) equal to the thickness of the microchannel (Figure 8-1(b)). The
no-slip boundary conditions are applied to both upper and bottom walls during
flow simulation. Constant flow velocity (e.g. 5mm/s) is specified at the inlet. The
outlet is assumed to be at atmospheric pressure. Moreover, we assume that the
upper wall is inert and does not adsorb DNA molecules. As seen in Figure 8-1(b),
the bottom wall of the microchannel is comprised of two parts: probe regions
where probe DNA molecules are immobilized at a concentration of 0Θ and
spacing areas which are bare glass surface. Both non-specific adsorption and
target hybridization will occur at probe regions while the spacing areas only
adsorb target molecules.
Figure 8-3 An example of meshed 2-D geometry of the microchannel. The grid closed to bottom wall was meshed with much higher density because it is close to the reactive surface with probe spots.
185
The 2-D geometry in Figure 8-1(b) was computationally discretized into
unstructured triangular cells as shown in Figure 8-3. The total number of mesh
elements is ~ 6000 for a typical model. The simulations were run on a HP
M8407C computer with 6 GB of RAM and an Intel® Core™2 Quad processor;
each simulation typically required ~5 min of computation time.
8.4.2 Parameter values used during simulation
During the non-dimensionalization processes, a series of parameters have
been used to scale the dimensionless variables. To verify and compare the
effectiveness of the model, the values of these parameters are extracted from
our experimental results and literature reports. For example, the characteristic
value of the microflow velocity (U) is picked from the experimentally-measured
average flow velocity and it ranges from 0.1 to 5mm/s. The channel height (H) is
set to 30 µm, which is a typical value used in our work [94]. The concentration of
the target DNA molecules varies from 0.1 nM to 1µM, as reported in our previous
works [94, 134]. We have estimated that the probe density ( 0Θ ) on the aldehyde-
modified glass surface is ~ 5 × 1011 strands/cm2 or 8.3 × 10-9 mol/m2 [94]. This
probe coverage is comparable to the values obtained elsewhere [139, 221, 250,
251, 327, 328]. The average radius occupied per probe molecule (Rp) is 7 nm.
In our model, the maximal surface concentration of non-specifically
adsorbed target molecules (ηmax) has been used in the non-dimensionalization
process. Because the adsorption of DNA is non-specific, a full monolayer of
targets could be considered as maximal at spacing region [309]. On the other
hand, probe regions are not fully packed with probe molecules, as calculated
186
from the probe density, and target DNA could adsorb to these regions as well.
Therefore, ηmax is given by [309]:
20
max 2
1 A p
A t
N RN Rπ
ηπ
− Θ= (30)
where NA is the Avogadro’s Number, Rp is the radius of a probe site, and
Rt are the gyration radius of an adsorbed target molecule. For 21-mer
oligonucleotides and longer single-stranded DNA (260 bases from denatured
PCR products), the calculated gyration radius are 2 nm and 7 nm, respectively
[329].
The diffusion of DNA molecules in bulk aqueous solution has been studied
extensively [59, 329-332]. According to the Stokes-Einstein correlation, the
diffusion coefficients of macromolecules (D) are proportional to temperature, and
they are inversely proportional to the bulk phase viscosity and to the
hydrodynamic radius, which is highly related to the molecular size [330, 333].
Lukacs et al. has suggested an empirical equation on the diffusion coefficients of
duplex DNA in water: D = 4.9 × 10-6 cm2/s · [base pair number] -0.72. The equation
is applicable to double-stranded DNA fragments with sizes of 21–6, 000 bp [59].
As for single-stranded DNA, the diffusion coefficients have been reported to
follow an empirical equation as: D = 7.38 ×10-6 cm2/s · [base number] -0.539 from
approximately 10 to104 bases at room temperature in water [331]. Moreover, it
has been reported that the diffusion coefficients are influenced by experimental
conditions. For instance, low ionic strength and the presence of fluorescent
187
labels on DNA molecules could reduce the diffusion coefficient, but by less than
one order of magnitude of difference [329, 334].
Surface diffusion can lead to the enhancement of the hybridization
efficiency of DNA microarray [305, 306]. This two-dimensional diffusion of DNA
molecules is usually slower than that in bulk solutions and it could be very
different on various surfaces. Chan et al. measured the surface diffusion
coefficients (Ds) of 21-base oligonucleotides on two types of silanized glasses:
APTES-modified and N-methyl- APTMS-modified, and they found that the
values ranged from ~1 ×10-9 to 7 ×10-9 cm2/s [306]. These values are applied to
the simulation of DNA hybridization in our work.
The adsorption and desorption parameters of oligonucleotide on various
types of glass substrate have also been measured by Chan et al. [306, 321].
From their results the value of adsorption equilibrium constant (Ka) can be
estimated at ~1×104 M−1 and the desorption rate constant (kd) between 0.15 and
0.45 s−1, depending on the substrate type. Because no other data is available for
predicting the adsorption behaviour of different DNA sequences, we assume that
these values are constant for the adsorption/desorption processes of any DNA
sequence on the glass surface.
The kinetics of the heterogeneous hybridization between bulk-phase
target DNA and the surface-immobilized probes was thought to be slower than
that of homogeneous solution hybridization due to steric interference [15].
Okahata et al. measured the kinetic parameters of oligonucleotide microarray
hybridization [16]. The effects of probe spacers, sequence length, ionic strengths,
188
temperature, and mismatch location have also been discussed. From their
results the value of hybridization rate constant (k3) can be estimated at ~1×105
M−1·s−1 and the denaturation rate constant (k-3) is ~2×10-4 s−1, for room
temperature hybridization of 20-mer oligonucleotides with 20-mer immobilized
probes. These values are of the same order with the experimental results from
other groups’ work using different measurement methods [15, 335-337]. In terms
of the rate constant of the 2-D hybridization (k2) from surface-adsorbed target
DNA, it can be estimated from the following equation [309]:
2
3
163
s
p
Dkk DRπ
= (31)
We assume that the denaturation rate constants of both bulk-to-surface (k-
3) and surface-to-surface (k-2) processes are equal.
189
8.5 Results and discussion
8.5.1 Bulk concentration profiles of static hybridization and microfluidic hybridization
The model was used to visualize the profile of bulk concentration (C)
around probe zones under static or flow hybridization. In conventional microarray
hybridization, if ~100µL of target solution was applied to an area of 20 mm × 20
mm on a glass slide printed with probe arrays [19], the thickness of the liquid film
is calculated to be 0.25 mm. On the other hand, in microfluidic hybridization,
~1µL of target solution is confined to a microchannel and flows over the probe
arrays. The depth of the microchannel is usually less than 100 µm. In our study,
microchannel plates with average height of 30 µm have been used [94]. By
solving the proposed model numerically, the bulk concentration (C) profiles after
3-min static and microfluidic hybridization of oligonucleotide targets are shown in
Figure 8-4(a) and (b), respectively. From the color map, it can be seen that the
target DNA concentration are consumed to a different degree along the bottom
wall during static hybridization (Figure 8-4(a)). The calculated sample
concentration at bottom wall (Cw) adjacent to the no-probe regions drops from 10
nM to 8.2 nM. This decrease in bulk concentration is due to the non-specific
adsorption of target molecules on the glass surface. At the probe regions, the
hybridization process significantly depletes the Cw down to 1.2 nM. On the
contrary, microfluidic flows prevent localized target depletion around probes by
continuous replenishment with fresh sample solutions. The lowest concentration
of bulk solution at bottom wall (Cw) is 9.6 nM after 3-min hybridization. Higher
190
local target concentration results in faster hybridization rate. Figure 8-4(c) shows
the simulated signal-to-time curves for 15-min hybridization. The average signal
is almost 3 times as high as that obtained from the static method at 15 min.
Figure 8-4 (a) Concentration profile of static hybridization. (b) Concentration profile of
microflow hybridization. The average flow velocity is 1 mm/s and the flow direction is shown as a blue arrow. In both (a) and (b), an array of 3 probe spots has been incorporated in the model. The probe region width and spacing are at 200 µm. The sample concentrations at inlets are set to 10 nM and the hybridization time is 3 min.The bottom rainbow bars denote the bulk concentration scale. (c) Kinetic curves showing the change of the hybridization fraction vs. time during the static or microflow hybridization in 15 min.
8.5.2 Prediction of the detectable range of oligonucleotide targets
The detection range of DNA microarray analysis depends upon the
performance of both the scanner and the microarray sensor. Although modern
scanners usually have a 16-bit digitization in signal outputs (216 = 65,536), the
actual dynamic range is less than 5 orders [338]. It is because the detection
range is confined by the probe coverage (upper limit) as well as the fluorescent
background (lower limit) of the solid substrate. Since the background signals
could take 2 orders in the detection of Cy5-labelled targets, the actual range of
1.2 nM
Concentration map of static hybridization
Flow
10 nM
9.6 nM 10 nM
0.25 mm
0.03 mm
(a)
(b)
(c)
Concentration map of microfluidic hybridization
0 200 400 600 800
0.0
0.2
0.4
0.6
0.8
1.0
Hybr
idiza
tion
fract
ion
Time (Sec)
Microfluidic Static
191
fluorescence signal detection in the microarray scanner thus spans only 3 orders
of magnitude.
To examine the detectable range of the microarray, oligonucleotide targets
at 100, 10, 1, 0.1, and 0.01nM were prepared and hybridized to the probe arrays
through microchannels. The resulted fluorescence images are shown in Figure
8-5(a). It was found that the hybridization signals obtained from 1µL of 100-nM
target solution was almost saturated. Higher concentration did not give significant
increase in fluorescence intensities. On the other hand, 1 µL of 0.01-nM targets
could not be detected at the experimental conditions. The signal-to-noise ratio
from the hybridization of 1µL of 0.1-nM target solution is ~6, which is close to the
detection limit. Therefore, the dynamic range of the oligonucleotide analysis
spans 3 order of magnitudes from 0.1~100 nM.
The experimental data can be compared with the simulation results from
the proposed model. As shown in Figure 8-5(b), the calculated relative
hybridization fraction is close to saturation ( * 1Θ = ) for 1µL of 100-nM oligo
targets after 12-min hybridization. This fraction decreases at lower target
concentrations. For instance, the number of hybridized DNA from 1µL of 0.1-nM
and 0.01-nM targets is around 1/260 and 1/3200, respectively, of that from 100-
nM targets (saturated hybridization). Since the scanner cannot read signals less
than 1/1000 of the saturated value (3 orders), it is impossible to detect 1µL of
0.01-nM DNA samples under the current experimental conditions. To achieve a
lower detection limit in concentration, further improvement on scanner
performance, probe capacity or different detection labels might be used.
192
Figure 8-5 (a) The image of hybridization patches by flowing through 1-µL oligonucleotide samples at different concentrations in 12 min. The hybridization patches from two vertical repeated probe lines are shown. (b) The normalized hybridization signal intensities from the experimental results in (a). The error bars come from the standard deviation of 5 hybridization patches. The simulated hybridization signals are also shown for comparison.
8.5.3 Effects of flow rates and channel dimensions on hybridization signals
In solution-phase hybridization, the time needed to reach thermodynamic
equilibrium depends only on reaction kinetics. On the contrary, in microarray
analysis, since probe molecules are immobilized on a solid surface, target
molecules in bulk phase have to be transported to the surface probe region by
diffusion before hybridization reactions. This diffusion procedure has been
proven to be a limiting factor due to the slow diffusion of DNA molecules [72, 81,
84, 126, 303, 310, 317]. Microfluidic method introduces additional mass transport
through convection and thus enhances the hybridization signal. This advantage
could be evaluated by the dimensionless Péclet number (Pe), which is the ratio
between the characteristic convection rate and diffusion rate. When Pe>>1, the
convective transport dominates over diffusion and localized depletion is
0.0001
0.001
0.01
0.1
1
100 nM 10 nM 1 nM 0.1 nM 0.01 nM
Rel
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atio
Target concentrations
Simulation
Experimental100 nM
10 nM
1 nM
0.1 nM
Oligo targets (a) (b)
193
eliminated, resulting in a fast mass transport. A high Pe number can be simply
achieved by flushing the target solution through the hybridization channel at a
high flow speed. However, at a fixed hybridization time, a faster flow will result in
a larger sample consumption compared to a slower flow, unless some
recirculation facilities are used to reduce the sample consumption [72-74]. On the
other hand, when the sample volume is fixed, the total residence time decreases
at high flow rates and the hybridization signal could be reduced. It is thus
important to find optimum flow rate for the quantification of microfluidic DNA
hybridization within small sample volumes.
We performed experiments at different flow rates to identify the effects of
mass transport on the hybridization events. The same amount of oligonucleotide
target solutions (1 µL) was introduced to the probe region by either stop flow or
dynamic flow. In the former method, hybridization time was set to 30 min, while
the actual hybridization time in the latter method depends on the flow rate used.
For instance, hybridization time of 1 µL at 0.1 µL/min was 10 min. The resulted
fluorescence images and signals are shown in Figure 8-6(a). As expected, it is
found that diffusion-limited stop-flow hybridization did not give a strong signal
even though the hybridization time is the longest. In terms of the dynamic
hybridization, although flow with the highest flow rate (2 µL/min) is least likely to
be diffusion-limited, it resulted in lowest hybridization signals. On the contrary,
flow with the lowest flow rate (0.1µL/min) in the experiment gave the highest
hybridization signals.
194
Figure 8-6 (a) The fluorescent image of microchannel hybridization results at different flow rates. Six flow rates, from left to right, 2.0, 1.0, 0.5, 0.3, 0.2, and 0.1 µL/min have been applied. The hybridization image in the right most is from 30-min stop-flow hybridization. 1 µL of 10-nM oligonucleotide samples were applied to each microchannel. (b) The relative hybridization intensities from the left image. The error bars are from the standard deviation of 5 hybridization patches.
These experimental results can be interpreted by the proposed model.
Four flow rates ranging from 0.01 to 10 µL/min were simulated and the
corresponding Pe values are from 10 to 10000. For 1 µL of sample solutions, the
hybridization time is calculated to be from 6 s to 6000 s, depending on the flow
rates. The stop-flow hybridization was also studied for comparison. Figure 8-7(a)
shows the average bulk concentration of targets adjacent to the probe regions
(Cw*) at the end of hybridization. It was found that the stop-flow method did
cause a significant local depletion of target DNA at the probe region. The relative
bulk sample concentration (Cw*) decreased to ~0.003 after 30-min hybridization.
On the other hand, even at the lowest flow speed (Pe = 10) it is sufficient to
eliminate the depletion, and the relative target concentration above the probe
0.0
0.2
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0.6
0.8
1.0
2.0 1.0 0.5 0.3 0.2 0.1 Stop
Flow rate (µL/min)
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inte
nsi
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(a) (b)
Sam
ple
flow
dire
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Flow rate (µL/min) 2.0 1.0 0.5 0.3 0.2 0.1 Stop
195
region is close to 0.75. In the other cases, although the flow speed is increased
up to 1, 000 times, this local concentration does not vary much and it goes up to
only 0.88 at Pe = 10, 000. Therefore, diffusion is not a limiting factor anymore
when Pe >10 and the hybridization signals depend on reaction kinetics instead.
Figure 8-7(b) shows the simulated hybridization fractions ( *Θ ) at different
flow rates. Because the sample volume is fixed to 1 µL, the reaction time is
inversely proportional to the delivery speed. Similar to the experimental data,
longer time results in higher signals and the highest hybridization fraction is
found at the lowest flow speed (Pe = 10). Nevertheless, the assay time is too
long in this case (~6000 s) and saturation occurs at ~2000 s; this approach could
be impractical for large sample volumes [339]. It is also found that the benefit on
hybridization fraction from slower flow velocity shows marginal improvement. For
example, a 10-fold decrease in the delivery speed from Pe = 10, 000 to Pe = 1,
000 results in an almost 10-fold increase in the hybridization signal. However, if
the flow speed decreases at the same ratio from Pe = 100 to Pe = 10, the
increase in the hybridization signal is less than 2 folds and this is at the expense
of 10-fold reaction time. Therefore, optimized flow speed with the consideration
of both the reaction time and signal intensities can be found around Pe = 100,
where the average flow speed is between 0.1~1 mm/s and the hybridization time
is at the level of 10 min with the 30-µm deep microchannel used in the
experiment .
196
Figure 8-7 (a) The simulated results of the relative bulk target concentrations adjacent to the probe regions. (b) The simulated hybridization kinetics at different flow conditions. The hybridization time for the stop-flow method is 30-min. In the dynamic flow method, four flow speeds, from left to right, 0.01 to 1 mm/s have been simulated and the corresponding Pe values are from 10 to 10000. 1 µL of 10-nM oligonucleotide samples were applied to each microchannel.
Reduction of channel height is another strategy to efficiently deliver target
molecules to the surface probes [134, 326, 340, 341]. At same flow speeds,
shallower microchannel results in a longer residence time as compared to deeper
channels. The increase of hybridization signals is thus expected due to longer
reaction time in the shallower microchannels. On the other hand, if the total
residence time are controlled to be the same for both types of microchannels, the
flow speed in shallower microchannels is thus higher, which results in an
increase in the convective flux (from higher flow speed). Moreover, the
characteristic diffusion time of target molecules in shallow channels is less than
that in deep channels, which will also benefit the surface hybridization. As seen
from the simulation results in Figure 8-8(a), the simulated hybridization signal
increases 17% by decreasing the channel depth from 75 µm to 24 µm.
(a) (b)
0.1 1 10 100 10001E-4
1E-3
0.01
0.1
1
Rel
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e hy
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izat
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fract
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Time (Sec)
Pe = 10 Pe = 100 Pe = 1000 Pe = 10000
0.001
0.01
0.1
1
Stopflow
Pe =10
Pe =100
Pe =1000
Pe =10000
Bu
lk c
on
cen
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t w
all
(Cw
*)
197
Compared to the experimental findings in Figure 8-8(b), the increase of
hybridization signals from shallower microchannels is even higher at ~50%. The
difference could be due to the further improvement from the stabilization effect on
hybridized DNA induced by microflow, i.e. the increase of flow speed might
benefit duplex formation [87, 342].
On the other hand, the reduction of channel or chamber height shows
adverse effect on static microarray hybridization. From the simulation results
shown in Figure 8-8(a), the hybridization signal decreases ~75% with the shallow
microchannel when using the stop-flow method. This is understandable because
less sample solutions are accommodated at the probe region and the local
depletion around the sensing area is even worse for shallower channels.
Figure 8-8 (a) The simulated hybridization intensities in microchannels of 2 different
depths. Here, 2 types of microchannels, 75 µm and 24 µm, are simulated and the hybridization time is 3 min in all cases. The Pe number of both types of microchannels is 1000. In stop-flow method, the hybridization time is set to 30 min. (b) Experimental results from flow hybridization of 1-µL samples in the 2 types of microchannels.
(a) (b)
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198
8.5.4 Effect of probe coverage on hybridization signals
In DNA microarray analysis, the probe DNA molecules are immobilized on
a glass surface, and then heterogeneous hybridization occurs when targets in
bulk phase hybridize with surface-immobilized probes. The hybridization signals
depend on the probe coverage in two ways. First, the maximal amount of
captured targets cannot exceed the amount of probe molecules at the sensing
region. Therefore, the higher is the probe density, the higher is the hybridization
capacity as well as the maximum hybridization signals. Secondly, the kinetics of
target capture process is affected by probe coverage. The current view of duplex
formation for short oligonucleotides is nucleation first, followed by helix zipping
[265]. For the target molecule to hybridize at the surface, it has to first penetrate
into the probe DNA film. Therefore, it is possible that lateral interactions with
nearby probe DNA molecules affect the kinetics due to steric constraints. In fact,
surface hybridization of tightly-packed probe molecules has been reported with
less efficiency than loosely-packed probes [112, 221, 335].
The effect of probe density on hybridization signals was evaluated with the
proposed model. Here, an equation proposed by Chan et al. was used to
estimate the relationship between probe coverage and the kinetic constant of
target DNA in bulk solution hybridized to surface immobilized probe molecules
[305]. The equation is shown as follows:
23
33
A pDN Rk
π χσ
= (32)
199
where NA is Avogadro constant, χ3 is the reaction success probability and it is
chosen as 0.001 [305], σ3 is the persistence length of the target DNA, and Rp is
the radius each probe molecule occupied. If we assume that there is no overlap
of probe molecules in the sensing region, Rp can be calculated using the
following equation:
0
1 12p
A
RN
=Θ
(33)
The higher is the density of the packed surface probes; the lower is the Rp value.
For the same DNA targets, the kinetic constant of surface hybridization (k3) is
inversely proportional to the density of surface probes. This relationship has been
confirmed experimentally by Michael et al.’s work, where they found that with
probe coverage decreased from 5.2 × 1011 to 1.38 × 1011 strands/cm2, the
hybridization kinetic constant increases almost 4 times from 0.9 × 105 to 4.3 ×
105 M-1·s-1 [335]. On the other hand, the reaction rate of denaturation did not
change significantly with the change of the probe coverage from the experimental
findings in Michel et al.’s work [335]. Therefore, an assumption that the k-3
remains constant for different probe densities is reasonable and is used in our
subsequent simulations.
Figure 8-9(a) shows both simulated and experimental results of the probe
coverage effect. As depicted in our previous work, the probe coverage on a glass
slide was controlled through using different concentrations of probe solutions
during spotting procedures [94]. The resulted probe densities vary from 2.3 ×
1011 to 7.9 × 1011 strands/cm2, which are comparable to the values obtained in
200
the studies by other groups [139, 221, 250, 251, 327, 328]. As seen in Figure
8-9(a), although the probe coverage increased almost 4 times, the hybridization
intensities from experimental measurements increased only around 1.5 times.
Moreover, no significant increase of hybridization signals was observed when
probe density is higher than 5.4 × 1011 strands/cm2. The results from simulation
are comparable to the experimental findings. The hybridization intensity
increased around 2 times and it reached a plateau after the probe density is
higher than 4.7 × 1011 strands/cm2.
The effect of probe coverage on hybridization is also described by the
simulated kinetic data. Because the kinetic constant of surface hybridization (k3)
is inversely proportional to probe densities, the lowest probe coverage resulted in
the fastest hybridization. As shown in Figure 8-9(b), the hybridization ratio ( *Θ ) is
saturated in the given time when the probe coverage is the lowest at 2.3 × 1011
strands/cm2 and the *Θ decreases significantly with the increasing probe density.
On the other hand, this dimensionless hybridization ratio is just a relative fraction
and it reflects the ratio between the hybridized probe molecules with the initial
number of the probe molecules ( *0Θ = Θ Θ ). To compare the hybridization
signals at different probe coverage, one has to multiply the ratio with the
corresponding initial probe density. Therefore, higher probe coverage can
provide higher surface concentration of un-hybridized probe molecules, which
could counteract the effect from lower kinetic constant, and the plateau shape in
Figure 8-9(a) is thus formed. The signals could be further enhanced when longer
hybridization time is used, as shown in Figure 8-9(b).
201
From Figure 8-9(a), it is also found that the simulated results give a higher
hybridization ratio compared to the experimental findings. This could be
attributed to the setting of the reaction success probability, χ3, in equation (42).
Though it is chosen as 0.001, it could be lower for diluted target solutions [305].
Figure 8-9 (a) The experimental and simulation results of the effect of probe coverage on hybridization signals. Top curve with triangle labels shows the simulated hybridization signals at different probe coverage; Bottom curve with square labels shows the experimental hybridization signals at different probe coverage. (b) The simulated kinetic curves of hybridization at different probe densities.
8.5.5 Assay conditions on the improvement of signal intensity and specificity/selectivity
In conventional microarray analysis, target solutions are usually incubated
with the surface-bound probes for static hybridization in 12-18 hours [19]. The
assumption behind this protocol is that the hybridization time is sufficiently long
and a thermodynamic equilibrium can be considered to be attained [343, 344]. In
this case, when non-specific adsorption and diffusion limitation of target
0 30 60 90 120 150 180
0.0
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0.4
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1.0
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ratio
Time (Sec)
2.3E+11 4.7E+11 5.4E+11 5.8E+11 6.5E+11 7.9E+11
0.5
1.0
1.5
2.0
2.5
2.3 4.7 5.4 5.8 6.5 7.9Probe density (×1011 Strands/cm2)
No
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(a) (b) Probe density (strands/cm2)
Experimental hybridization signals
Simulated hybridization signals
202
sequences are neglected, the equilibrium fraction of hybridized duplexes ( *eqΘ )
can be described by the Langmuir model [345]:
*'
0 3 3 0 3
1 11 1
eqeq k k C K−
ΘΘ = = =
Θ + + (34)
where '3K is the dimensionless equilibrium dissociation constant define in
equation (26). It is obvious that the more stable is a DNA duplex (lower '3K ), the
more is the amount of target sequences hybridized on a probe spot ( eqΘ ). The
equilibrium constant is calculated from the Gibbs free energy of duplex formation
(ΔG) via ( )31 expK G RT= −∆ and ΔG has been quantitatively described by the
nearest-neighbour model [30, 346-348]. In DNA microarray applications, it is
common that multiple probes and/or multiple samples are involved on one chip.
Non-match and mismatch (MM) duplexes are usually less stable than perfect-
matched (PM) duplexes due to the less number of hydrogen bond interactions
(as seen in Figure 8-10). These duplexes can be discriminated from PM
duplexes by the comparison of the signal intensities, which are linked to the
hybridization fractions (Θ ) at the probe regions.
203
Figure 8-10 Sequence structures showing (a) a perfect-matched duplex (B-B’) and (b) a one-base-pair-mismatched duplex (B-NB’) from two 21-mer oligonucleotides.
Table 8-1 lists the thermodynamic data from 6 groups of DNA duplexes.
Each group includes a 21-bp perfect-matched duplex and a similar one with
single-base-pair-mismatch at the duplex center. The central three base pairs of
the mismatched duplexes are listed in the table to show the mismatch types. The
thermodynamic data are calculated based on the nearest-neighbour model [30,
349]. The equilibrium dissociation constants (K3’) of mismatched and perfect-
matched duplexes are compared by ratios. From the thermodynamic data it can
be seen that the most stable molecules among the 12 DNAs is the perfect-
matched J duplex (ΔG = -91.2 kJ/mol) while the mismatched L duplex shows the
biggest free-energy difference (The equilibrium constant ratio is 577) from its
perfect-matched fellows.
(b) (a)
204
Table 8-1 The calculated free energies of 6 groups of DNA duplexes.
Duplex name
Mismatched part for MM duplexes
ΔG of PM duplex
(kJ/mol)*
ΔΔG of PM and MM
duplexes (kJ/mol)**
'3'3
(MM)(PM)
KK
B ATA:TTT -71.5 10.04 32
J TCA:ACT -91.2 15.89 242
K GGG:CTC -76.9 7.11 12
L TAC:ACG -84.1 18.4 577
M GGG:CTC -79.5 7.11 12
N CCC:GAG -82.8 14.22 136
* Calculated at 50°C and in 0.4M NaCl using the DINAMelt Web Server [349]. ** ΔΔG = (ΔG of MM duplexes) – (ΔG of PM duplexes).
In the microfluidic method, the equilibrium time of surface hybridization
has been reduced since the diffusion limitation of target molecules is eliminated.
However, the time required to reach thermal equilibrium may still exceed the
assay time, e.g. 3 min. In this situation, the discrimination ratio between perfect-
matched (PM) and mismatched (MM) DNA may not be predicted accurately by
the comparison of ΔG values. For instance, the experimental results of the above
6 groups of DNA duplexes from 3-min microfluidic hybridization (shown in Figure
8-11) are not consistent with the free energy data. The most stable DNA (duplex
J) did not appear as the one with the highest hybridization intensity. Despite that
the perfect-matched B duplex has a similar free energy (ΔG = -71.5 kJ/mol) with
205
that of the mismatched M duplex (ΔG = -72.4 kJ/mol), the hybridization signal
from the target B DNA is almost 10 times of that from the target M DNA.
Furthermore, the discrimination ratio is not related to the K3’ ratio. For
example, the experimental findings do not support the expectation that the
PM/MM duplexes of N should have a better discrimination ratio, as compared
with the PM/MM duplexes of B and K. Moreover, the signal intensities for L
duplexes are considerably low and there is even a false discrimination for the
mismatched duplexes. The experimental results indicate that the hybridization
efficiency and discrimination ratio of DNA duplexes cannot be reliably predicted
with the calculated thermodynamic equilibrium data.
Figure 8-11 The experimental hybridization results from the microfluidic hybridization of 6 groups of DNA. Each group represents two targets with one-base difference at the sequence center and the probe molecules are complementary to one of them. The 12 DNA solutions were hybridized in separated microchannels but under the same conditions at ~50°C and in 2.5x SSC for 3 min.
0.0
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B J K L M NDifferent duplexes
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Mismatched duplexes
Perfect-matched duplexes
206
For fast DNA analysis on microfluidic chips, kinetic constants for both
forward bulk-to-surface hybridization (k3) and reverse denaturation (k-3) dominate
signal intensity and selectivity. With the proposed model, we evaluate the effect
of these two kinetic constants on the intensity and selectivity of microarray
hybridization. As given in equation (26), k3 has been nondimensionalized to a
Damköhler number (Da3), to compare the effect from the duplex dissociation, k-3
is also non-dimensionalized to a dimensionless Damköhler number, Dn, and it is
a ratio of characteristic diffusion time and duplex dissociation time.
3 0
0
Characteristic diffusion timeCharacteristic duplex dissociation time
k HDnC D− Θ= = (35)
The dimensionless dissociation equilibrium constant ( 3 'K ) is then obtained
by
' 33
3 0 3
k DnKk C Da
−= = (36)
The two Damköhler numbers (Da3 and Dn,) were arbitrarily assigned to 6
values ranging from 0.001 to 100 where most of the experimental values could
fall in this range. The hybridization time are set from 3 min to 60 min to mimic
typical microfluidic hybridization times. The results are shown in Figure 8-12.
207
Figure 8-12 The simulated effect of the 2 Damköhler numbers (Da3 and Dn) on relative hybridization fraction after (a) 3-min, (b) 15-min, and (c) 60-min microfluidic hybridization. The corresponding dimensionless dissociation equilibrium constants (K3') are also shown as dashed lines in the 3 graphs. The colorscale bar beside each graph denotes the level of the relative hybridization fraction.
As the value of K3’ (dimensionless equilibrium dissociation constant)
decreases from 1000 to 0.001 (as represented by the light-blue dash lines in the
figures), DNA duplex is more stable and the hybridization intensity increases in a
general trend (shown as colour maps). For a certain combination of Da3 and Dn
numbers, longer hybridization time usually results in higher signals, as seen from
Figure 8-12(a) to (c). Therefore, if only the signal intensity is considered, any
1E-3 0.01 0.1 1 10 1001E-3
0.01
0.1
1
10
100
DN n
umbe
r
Da number
0.00.10.20.30.40.50.60.70.80.91.0
1E-3 0.01 0.1 1 10 1001E-3
0.01
0.1
1
10
100DN
num
ber
Da number
0.00.10.20.30.40.50.60.70.80.91.0
1E-3 0.01 0.1 1 10 1001E-3
0.01
0.1
1
10
100
DN n
umbe
r
Da number
0.00.10.20.30.40.50.60.70.80.91.0
(a) (b)
t = 3 min t = 15 min
t = 60 min (c)
208
experimental condition that can promote duplex association (higher 3k ) and can
stabilize the DNA duplexes (lower 3k− ) will boost the hybridization fraction.
On the other hand, if multiple samples are to be hybridized to the same
probe arrays, it would be desirable if PM and MM DNA duplexes can be
discriminated from each other by the difference in signal intensities. For two
target sequences of completely different sequences, the difference in the free
energy of duplex formation with the same probe sequence is very large and it
has no problem in discrimination. However, for duplexes with only a couple of
mismatched base pairs, the difference of duplex formation free energy (ΔΔG)
from the perfect-matched ones could be as low as ~7 kJ/mol (as shown in Table
8-1) and the calculated equilibrium constants only differ by ~1 order of
magnitude. In this case, their thermodynamic behaviours alone are not sufficient
to produce the successful discrimination of these two sequences. For example, in
Figure 8-12(a), even when two duplexes with different dissociation equilibrium
constant (K3' = 0.001 and 0.01, respectively), the fraction of hybridization could
be similar at 0.2~0.3 after 3-min hybridization and it would be very hard to
discriminate between these two target sequences.
The selectivity between the PM and MM DNA duplexes could be improved
by including the hybridization kinetics during the study. During the short-term 3-
min hybridization, Da3 (duplex association kinetics) has more impact on
hybridization signals as compared to Dn (duplex dissociation kinetics). For
example in Figure 8-12(a), if the Da3 number is fixed at 1, the fraction of
hybridized molecules increases a little from 0.1 to 0.3 while the Dn number
209
decreases 6 order of magnitude from 100 to 0.001. On the contrary, if the Dn
number is fixed at 0.01, which is a common value for surface-bound DNA, the
fraction of hybridized molecules increases from 0.1 to saturated when the Da3
number increases for 2 orders from 1 to 100. The duplex dissociation kinetic
constant (Dn) starts to take effect in longer-term reactions such as 15-min and
60-min hybridization (Figure 8-12(b) and (c)). During DNA microarray analysis,
experimental conditions such as pH, ionic strength, additives, temperature, and
sequence compositions show different impacts on the two kinetic rate constants
(Da3 and Dn) [10, 16, 350]. By carefully choosing the combination of assay
conditions, discrimination between the perfect-matched and mismatched targets
could be achieved.
Another condition to achieve mismatch discrimination and to get rid of
non-specific adsorption before final image analysis is to rinse the hybridized
spots with buffers of lower ionic strength [19]. The proposed model confirms the
importance of this washing step in the discrimination of PM/MM duplexes and in
the alleviation of non-specific cross hybridization. Here, a different initial condition
was applied in which the probe spot was fully occupied by target molecules first
and blank buffer solutions (C0 = 0) were then introduced. Because the
microfluidic flow continuously replenishes the channel, all the dissociated
molecules will be removed immediately from the probe region. Figure 8-13
depicts the kinetics curves of this washing step, where the effect of different Dn
values is compared. The Dn number of the top curve (Dn = 0.1) is a typical value
of perfect-matched 20-mer duplexes. The simulation of the rest of the curves
210
represents the washing procedure on the less stable duplexes with higher Dn
values. These values were arbitrarily assigned with respect to the top one from
perfect-matched duplexes. It can be seen that washing with blank buffer did not
lead to substantial loss of the PM duplexes. After 3-min washing, the duplex
fraction is 95% of the initial value. However, the signal loss is more significant for
less stable targets. For the dissociation constant of 10-times higher than that of
PM duplexes (Dn = 1), 3-min washing results in 30% of signal loss. Since the
dissociation kinetic constant of the non-specific bound targets is usually 100-fold
of that of the perfect-matched ones [16, 306], the microfluidic method can
effectively wash away the non-specific bound DNA molecules in a short period.
Figure 8-13 The kinetic curves of the microchannel washing procedure at different dissociation constants. In all the cases the Da values were set to 1, which is a typical value for 20-mer duplex formation.
8.5.6 Spot morphology
The quantification of DNA microarray hybridization results relies on the
image analysis of the hybridization spots on microarrays. For automated
microarray image processing, an “ideal” microarray image is usually
0 200 400 600
0.0
0.2
0.4
0.6
0.8
1.0
Rela
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hybr
idiza
tion
fract
ion
Washing time (Sec)
Dn = 0.1 Dn = 0.2 Dn = 0.5 Dn = 1 Dn = 2 Dn = 5 Dn = 10
211
characterized by a low background intensity with minimal artifacts, pre-defined
spot shape (morphology), and distinct spot intensity with minimal uncertainty and
minimal deviation between repeated spots [351].
As shown in Figure 8-14(a), one of the irregularities often seen in pin-
spotted microarray images is donut-shaped spots with the signal intensity high at
the spot edge and low at the spot centre [352, 353]. On the other hand, when
microchannel probe spotting and intersection approach for hybridization are
used, this irregularity appears as sandwich shapes for rectangular spots (Figure
8-14(b)). The presence of a donut or sandwich-shaped intensity pattern leads to
high variation per spot and creates extra difficulties in subsequent image analysis
[354].
Figure 8-14 (a) Top: The fluorescence image of the hybridization results from pin-spotted DNA microarray. Bottom: The fluorescence intensity along the yellow dashed line in the top image. (b) Top: The fluorescence image of the stop-flow hybridization results from channel-spotted DNA microarray. Here, the sample channel was in horizontal and crossed two vertical probe lines. Bottom: The fluorescence intensity along the yellow dashed line in the top image.
0
2000
4000
6000
8000
10000
Distance
Rel
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uor
esce
nt
un
it
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500
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2000
Distance
Rel
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esce
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un
it
(a) (b)
1 mm 1 mm
212
For pin-spotted DNA microarray, one possible reason of the donut-shaped
spots is the fast evaporation process and the fixation of the contact line during
probe spotting stage [355, 356]. Microfluidic spotting method effectively
circumvents the above problems because the probe solution is confined within
microchannels and it is washed away after immobilization without dry-out.
Nevertheless, we still observed sandwich-shaped spots in stop-flow hybridization
in microchannels as seen in Figure 8-14(b).
Another cause for the occurrence of donut patterns on DNA microarrays is
diffusion limitation [352]. During static hybridization in microchannels, target
molecules diffuse from bulk solution to the probe surface in both vertical and
horizontal directions. Because the ratio of channel length and height is much
higher than 1, the sample molecules in bulk solution right above the spot surface
will be depleted in a short time (Figure 8-4(a)) and most of the target molecules
approach the probe spot from both sides. Before moving over the spot surface
and reaching the center of the spot, these molecules will have more chances to
bind to the edges of the spot and hence the donut/sandwich effect. The dynamic
hybridization method promotes mass transport by introducing extra convection
flow. If target molecules can be replenished immediately by the convection flow
of bulk solution (As shown in Figure 8-4(b)), the non-homogeneous donut
patterns are less likely to be formed.
Dimensionless numbers can provide an estimation of the combined effect
from different process variables on hybridization in diffusion- and convection-
driven DNA microarray systems. The non-homogeneity pattern of hybridization
213
spots is due to the diffusion limitation of target molecules, and microfluidic
hybridization could improve the spot morphology through the convection effect.
To evaluate the minimal convection rate needed to achieve a homogeneous
hybridization spot, we combine the Da number and Pe number together to get a
dimensionless ratio of the characteristic convection rate to the hybridization rate,
i.e.,
3 0
Characteristic convection rateCharacteristic hybridization rate
Pe UDa k
= =Θ
(37)
With the proposed model, we simulated the profiles of bulk target
concentration at the bottom wall (Cw*) as well as the hybridization signal along
the probe region. As shown in Figure 8-15(a), the profiles of bulk concentration at
bottom wall for static hybridization is reversely bell-shaped. The target DNA
molecules are almost depleted near the center of probe region. Due to the non-
specific adsorption, the bulk concentration at the rest part of the bottom wall is
also less than the initial concentration. On the other hand, the target
concentration profile for dynamic hybridization is asymmetric. At the left of the
probe region, the bulk concentration is very close to the initial value because of
the replenishment from the convection flow. The target concentration at bottom
wall drops along the probe region due to the hybridization event and is recovered
later at the no-probe region. The lowest target bottom concentration occurs at the
right edge of the probe region and the degree of the concentration drop depends
on the ratio between the convection rate and hybridization rate. When the flow is
fast enough, Pe/Da>1000, which corresponds to a flow speed at ~1mm/s for
214
oligonucleotide sample in the 30-µm microchannel, the target concentration drop
is less than 10% from the initial bulk concentration.
Figure 8-15(b) shows the hybridization fractions ( *Θ ) along the probe
region from static and dynamic hybridizations with different Pe/Da ratios. The
relative standard deviation (RSD) of the hybridization signal across the probe
region in static hybridization is near 40% and a donut-shape spot is thus
expectable. For dynamic hybridization method, the asymmetric distribution of the
bulk concentration at the bottom wall results in asymmetric hybridization fractions
across the probe region. We have observed this type of hybridization spot during
experiments at slower flow rates. Under faster flow conditions, such as Pe/Da >
1000, this non-homogeneity can be considered as negligible in subsequent
image analysis because the RSD of the hybridization signal change across a
hybridization spot is less than 5%.
215
Figure 8-15 (a) The simulated relative bulk concentration profile of target DNA at the bottom wall with a probe spot. Here, both static and dynamic hybridizations are simulated. For the latter method, 5 different flow rates were tested resulted in 5 Pe/Da ratios. (b) The simulated hybridization fraction profiles at the bottom wall with different hybridization methods. In all cases, the hybridization time is set to 3 min.
The non-homogeneous patterns could be eliminated when using PCR
products or narrow probe lines. Compared to the short oligonucleotides, the
hybridization kinetics of longer PCR amplicons is slower and the Pe/Da ratio is
thus higher. Our experimental data have confirmed that the sandwich pattern has
not been found for PCR targets under stringent hybridization conditions even
using the stop-flow method. In addition, the narrower probe lines also reduce the
non-homogeneity of the hybridization spots. Figure 8-16 compared the simulated
hybridization results on 5 probe lines with widths ranging from 50 µm to 1mm.
For static hybridization, if the probe lines are wider than 100 µm, the non-
homogeneity of hybridization spot is significant (Figure 8-16(a)). However, when
the probe line is as narrow as 50 µm, the signals along the probe region become
uniform and the RSD of hybridization intensities is less than 5%. The simulation
(a) (b)
0.0
0.2
0.4
0.6
0.8
1.0R
elat
ive
bulk
con
cent
ratio
n a
t bot
tom
wal
l
Distance (mm)
Pe/Da = 10000 Pe/Da = 1000 Pe/Da = 100 Pe/Da = 10 Static hybridization 0.0
0.1
0.2
0.3
0.4
0.5
Rel
ativ
e hy
brid
izat
ion
fract
ion
Distance (mm)
Pe/Da = 10000 Pe/Da = 1000 Pe/Da = 100 Pe/Da = 10 Static hybridization
216
results have been partially validated by the experimental data, where 50-µm
probe lines gave homogeneous hybridization patch after stop-flow hybridization
(Figure 8-16(a) insets) and 1-mm probe lines showed sandwich-like patterns
(Figure 8-14(b)). By further calculation, it is found that the diffusion time for a
target molecule moving over the probe spot is comparable to its characteristic
hybridization time, leading to a more uniform hybridization.
For dynamic hybridization, although the signals are asymmetric along the
probe region, the variation is not as high as that of the static hybridization. In all
the cases, the RSD of the hybridization signal change across a hybridization spot
is less than 10% (Figure 8-16(b)).
Figure 8-16 The simulated hybridization fractions along the bottom wall with a probe region. The width of the probe region varies from 50 µm to 1mm. (a) Static hybridization. The insets show the experimental results from the hybridization of oligonucleotide samples with complementary probe lines with a width of 50 µm. The concentration of the oligonucleotide samples is 100, 10, and 1 nM, respectively, from left to right. (b) Dynamic hybridization.
Rel
ativ
e hy
brid
izat
ion
sign
al in
tens
ities
Cross distance (mm)
Rel
ativ
e hy
brid
izat
ion
sign
al in
tens
ities
Cross distance (mm)
(a) (b)
300 µm
200 µm
100 µm
50 µm
1 mm
300 µm
200 µm
100 µm
50 µm
1 mm
217
8.5.7 Signal variation from spot to spot
During DNA microarray fabrication and analysis, small defects on the chip
substrate such as surface scratches or particles may appear, which results in
fake signals and interferes with subsequent spot quantitation [19, 65]. Therefore,
it is necessary to use repeated probe spots/lines to correct for these possible
errors. In practice, these spots with the same type and density of probe
sequences are usually next to each other in geometry for the ease of image
analysis. However, if they compete for the target molecules in an unequal way,
hybridization performance on these repeated spots are no longer equal and the
resulted signals are thus biased. For example, during the static hybridization, a
depletion layer around the probe spot evolves as time elapses and the
concentration of target molecules in this layer is much smaller than that in bulk
solutions, as depicted in the previous section. If the repeated probe spots are
very closed to each other, the depletion layer could eventually override the
spacing between probe spots (as shown in Figure 8-17(a) and (b)). For the spots
at the center of the probe groups, the average hybridization signal will be lower
than those at the rim especially after long-term incubation (Figure 8-17(c)).
218
Figure 8-17 Simulated graphs showing the evolvement of bulk concentration profiles with a group of 3 probe spots. (a) After 1-min static hybridization. (b) After 15-min hybridization. (c) Simulation results showing the evolvement of the discrepancy of hybridization fractions on the 3 probe spots at different time.
The signal variation from repeated probe spots appears in a different way
for microfluidic dynamic hybridization because the localized depletion around the
probe groups is negligible as depicted previously. Here, an extreme condition
was tested where 10 repeated probe lines were hybridized with oligonucleotide
samples of different concentrations. From the experimental results shown in
Figure 8-18, it was found that the signal intensities did not vary considerably for
the sample prepared in low ionic strength or stringent buffer solutions (1xSSC
buffer). For example, the RSD of the signals from 10 hybridization spots is 11%
and 7%, for 100-nM and 10-nM targets prepared in 1xSSC, respectively.
However, in a less stringent buffer (4xSSC), if the target concentration is less
than 10 nM, a unidirectional decrease in signal intensity along the flow path was
0.0
0.1
0.2
0.3
0.4
0.5
1 2 3
Re
lati
ve h
ybri
diz
ati
on
fra
ctio
n
1 min3 min5 min10 min15 min
Static hybridization at 1 min
Static hybridization at 15 min
1.1 nM 6.6 nM
(a)
(b)
(c)
2.0 nM 10 nM
219
observed and the variation from spot to spot is as high as 20%. The experimental
data can be interpreted by the model.
It is well known that DNA-DNA hybridization is highly dependent on the
ionic strength of bulk solutions as measured by [Na+] [12, 16]. High ionic strength
buffer is usually considered as less stringent and results in higher hybridization
signals. Moreover, Studier et al. have found that the hybridization rate in low-salt
concentration (<1.0M) is proportional to the cube of [Na+] [12]. The dependence
of the hybridization rate becomes less steep in higher salt concentration.
Because the salt concentration in our work ranges from 0.15M NaCl to 0.6M
NaCl, this cubic relation of [Na+] has been used during simulation. As seen in the
simulated concentration profile in Figure 8-18(c), fast hybridization kinetics in
high ionic strength buffer significantly depletes the target concentration in the
liquid front and the bulk concentration decreases along the flow path. Because
the probe spots at the right keep reacting with targets of lower bulk
concentration, the hybridization signals are systematically lower than those at the
left. The position-related hybridization signal could have an adverse effect on the
comparison of signals from different samples. Therefore, low stringent or high
ionic strength condition should be avoided especially in the discrimination of
short oligonucleotides using the microfluidic approach.
220
Figure 8-18 The experimental results from the microfluidic hybridization of oligonucleotide samples at 4 concentrations. (a) Samples are prepared with 1x SSC. (b) Samples are prepared with 4xSSC. 0.1-nM targets were not detected in (a). The bottom numbers represent the probe row number. (c) and (d) show the simulated profile of bulk concentration during hybridization in 4x SSC and 1x SSC buffer, respectively.
Targets in 4xSSC
1.E+00
1.E+01
1.E+02
1.E+03
1.E+04
1.E+05
R1 R2 R3 R4 R5 R6 R7 R8 R9 R10
Rel
ativ
e Fl
uore
senc
e U
nit
Targets in 1xSSC
1.E+00
1.E+01
1.E+02
1.E+03
1.E+04
1.E+05
R1 R2 R3 R4 R5 R6 R7 R8 R9 R10
Rel
ativ
e Fl
uore
senc
e U
nit
(a) (b)
0 nM 10 nM Concentration map from microfluidic hybridization
Flow direction
Flow direction (c)
(d)
100 nM
10 nM
1 nM
0.1 nM
221
8.6 Conclusions
Our results highlight the importance of incorporating physiochemical
factors and microchip parameters in both the design and the data analysis of
microfluidic DNA microarrays. Through dimensional analysis and numerical
simulations, we demonstrate that, (i) Convective transport is an efficient way to
enhance the kinetics of diffusion-limited hybridization; (ii) The detection range of
a DNA microarray is predictable with the proposed model; (iii) Fast flow rate is
not necessary and a Pe number of 10 is high enough to eliminate the diffusion
limitation; (iv) Low probe coverage facilitates surface reaction but limits
hybridization capacity; (v) Thermodynamic data of DNA duplex formation cannot
be used directly for the prediction of hybridization fraction, especially for short
time flow hybridization; (vi) The hybridization spot morphology and the signal
variation from spot to spot depend on the microchannel geometry, flow
conditions, as well as hybridization kinetics. The proposed model could be
extended for the design and characterization of all relevant microfluidic device
prototypes involving surface reactions.
222
9: CONCLUSIONS AND PERSPECTIVES
9.1 Concluding remarks
Hybridization on DNA microarrays has been a versatile technique in
genomic research. Because of their flexibility and low production cost,
microarrays with low-density probes have been used in nucleic acid diagnostic
applications as well as single-nucleotide polymorphism detections. Recently,
microfluidic technology has been combined with DNA microarray method through
an intersection approach. Here, probe molecules are immobilized microfluidically
as probe lines on substrates and DNA samples hybridize at intersections with
orthogonally positioned microchannels. This intersection microfluidic microarray
method avoids the exact alignment of the hybridization microchannels and the
spot shape is more regular for later image analysis. The method shows the
advantages of less sample usage, fast reaction kinetics, as well as multiple
sample capability. Moreover, higher throughput analysis has been achieved by
the use of centrifugal pumping with a CD-like microchip. This method utilizes the
body force from liquid itself and it is free of additional solution interface contacts
such as from electrodes or syringes and tubing. Centrifugal force driven flow also
features the ease of parallel reactions. This thesis contributes to the application
of the microfluidic DNA microarray method under three different topics described
as follows.
223
9.1.1 Microfluidic surface hybridization
In Chapter 3, some fundamental aspects regarding microfluidic surface
hybridization were studied on rectangular chips. The probe densities on the
glass substrates at different spotting conditions were evaluated and the numbers
were applied to the later theoretical modeling. In Chapter 6, the hybridization
behaviours of DNA targets with two fluorescent labels, fluorescein and Cy5, were
studied and compared. It was found that sample DNA with Cy5 labels showed
less photo-bleaching effect as well as much lower detection limit. In Chapter 3,
integrated temperature control was realized with a Peltier chip and was used
successfully in mismatch DNA discrimination. In Chapter 4, the need of
temperature stringency during mismatch discrimination was further relieved by
pre-binding the target DNA with gold nanoparticles. This form of discrimination
has not been previously described in the microfluidics community.
9.1.2 Applications and modeling of the CD-like chip using centrifugal pumping flow
In previous work from our group, a CD-like chip format was invented
where centrifugal pumping was used in the intersecting microchannel
hybridization. Chapter 5 and Chapter 6 further developed the concept. The
quality of the CD-like chip was enhanced with improved manufacture processes,
where high-resolution photomasks were used and SU8 coated on a silicon wafer
directly acted as the molding master. The resulted polymer channels are
smoother with better sealing with the glass substrate. As a result, the flow rate
variation from channel to channel was improved and the liquid movement was
224
controlled at a slower spin rate. Moreover, it is also found the channel geometry
affects the hybridization and shallower channels gave higher hybridization
signals. With all these improvements, 3-min detection and discrimination of 1-
femtomol PCR amplicons were achieved on the microchip for the first time.
Chapter 7 describes the experimental measurement and mathematical
modelling of centrifugal-pumping flows in the CD-like microchip. It is
demonstrated that steady flow has been attained with the equiforce spiral
channel design. The flow velocities and residence time of solutions have been
predicted with both a mathematical model and computer simulation. In contrast to
radial channel designs, liquid flow in the spiral microchannels is more
manipulatable and the residence time of the liquid is much extended. With
modifications, this flow dynamics study could be adapted to the modeling and
simulation of other centrifugal-pumping microflow systems.
9.1.3 Modeling and simulation of microfluidic hybridization kinetics.
As a complement to the previous experimental investigations, Chapter 8
provides a theoretical modeling and simulation of microfluidic DNA microarray
hybridization kinetics. Four questions have been answered in this chapter. (1)
For a given amount of sample (usually at ~10 nM and with a volume as small as
1 µL) and chip configuration, what would be the optimal flow rate to achieve the
highest-possible hybridization fraction? (2) Lower probe coverage facilitates
hybridization kinetics but also decreases the hybridization capacity, what would
the balanced values be? (3) Can we use the thermodynamics data of solution
hybridization to predict microfluidic microarray hybridization behaviour? (4) What
225
are the reasons of the observed non-homogeneous hybridization spots and
signal variation from spot to spot? The simulation results provide useful device
design criteria for the experimentalist to predict and control the behaviour of a
microfluidic DNA microarray experiment given its geometry and operation
conditions. Moreover, the proposed model and simulations are transferable to the
analysis of other surface-based biosensors.
9.2 Outlook and research perspective
9.2.1 Sensitivity
The main aim of the project is to develop a robust biochip platform with
good sensitivity for fast DNA analysis. Signal enhancement has been achieved
by flow hybridization in microchannels. In addition, hybridization capacity and
kinetics are highly dependent on the surface chemistry parameters and target
accessibility to immobilized probes [112]. As compared to planar surfaces, we
have developed a submonolayer of gold nanoparticles on glass substrate for
probe immobilization and the hybridization of oligonucleotide targets was
enhanced [95]. Other methods to increase surface area are also available. For
instance, microbeads present a larger surface capacity for probe immobilization
as well as faster target hybridization kinetics [357]. The sensitivity of DNA
detection could be further improved by the introduction of microbeads to the
current system.
226
9.2.2 Selectivity
In terms of selectivity, the advantages of gold nanoparticles have been
demonstrated in the discrimination of perfect-matched and mismatched
duplexes. However, only central-mismatch duplexes have been examined so far.
Further experiments on the discrimination efficiency of gold nanoparticles on
different mismatch types are to be studied. Moreover, the effect of nanoparticle
sizes on the discrimination efficiency is also an interesting subject.
9.2.3 Integration and packaging.
Research in microfluidic technology often shares the profit from the
development of microelectronics industry. Without exception, the centrifugal
microfluidic platform aims to utilize the well-developed compact disk (CD) system
[147, 148, 280]. The rotor driven/control system of the optical drive could be
revised to adapt to the need of microflow pumping. The current bulky and
complex scanner could be replaced by the laser head, lens, and optical pick-ups,
although their movement have to be reprogrammed since the hybridization
patches are positioned along spiral or radial paths. Moreover, hybridization data
could be collected in a more efficient way. All these studies will satisfy the quest
for miniaturization, faster analysis and the highest possible degree of integration
and eventually lead to the advent of portable microfluidic devices for high
throughput DNA assays.
227
9.2.4 Modeling and simulation of centrifugal-pumping flows
During the mathematical modeling of the centrifugal pumping flows, the
analysis has been focused on the spiral part of the microchannels. Under a high
rotation speed, such as 2400 rpm, the difference between the predicted and
experimental values of flow velocity is not negligible. We speculate that this
difference can be attributed to the extra pressure from the neck channel outside
the spiral part. Future studies could thus be pursued on the problem, which
would be helpful in estimating the effect of the microchannel connection between
different geometries on microflow behaviours.
9.2.5 Modeling and simulation of hybridization kinetics
The proposed kinetics model in Chapter 8 can be further modified for the
microfluidic microarray hybridization of PCR products in which inter-conversion
among multiple components in bulk solutions is considered. Unlike single-
stranded short oligonucleotide samples, PCR products are double-stranded DNA
with a much longer length of 100~1000 bp. Before hybridization analysis, they
have to be denatured at 95°C to break most of the duplexes into two
complementary single-stranded DNA. During microarray hybridization, the PCR
products in bulk solutions could appear in two formats: linear or loose-coiled
single-stranded DNA (LC) and renatured double-stranded duplexes (DX). The
two formats are in equilibrium to each other, see equation (1). If there is any
secondary structure on the single-strand molecule, a supercoiled form (SC) will
possibly be produced, see equation (4) [358, 359]. Therefore, the bulk sample
solution of PCR products could be a mixture of three or more components rather
228
than a single component as in oligonucleotide samples. Obviously, only DNA in
the linear or loose-coiled single-stranded form could hybridize to the immobilized
probes. On the other hand, the complementary strands could compete with the
immobilized probe DNA for the labelled target strands. Moreover, the possible
secondary structure of the single-stranded target also decreases the effective
concentration of the target strands. Therefore, the surface DNA hybridization
model can be modified to reflect the above situations.
The kinetic model in the study assumes that these DNA forms interconvert
and hybridize according to the mechanisms given as below:
dx
dx
kcomp k
LC LC DX−
+
(1)
and the kinetic equation is
LCdx DX dx LC LC comp
dC k C k C Cdt − −= − (2)
where CLC and CLC-comp are the bulk concentration of the single-stranded
target DNA molecules and their complementary strands, respectively. kdx and k-dx
are the hybridization and denaturation rate constant of the self-hybridization
process in bulk phase, respectively. For symmetric PCR amplification, which has
been used in our experiments, CLC = CLC-comp = C, therefore,
2dx DX dx
dC k C k Cdt −= − (3)
For the formation of the secondary structure leading to the supercoiled
form,
229
sc
sc
k
kLC SC
−
(4)
the kinetic equation is
sc SC scdC k C k Cdt −= − (5)
where CSC is the bulk concentration of the super-coiled target DNA
molecules. ksc and k-sc are the formation and dissociation rate constant of the
supercoiled form in the bulk solution, respectively.
The overall diffusion-convection-reaction model in 2-D microchannel for
linear single-stranded target molecules is written as:
2 22
2 2 dx DX dx sc SC scC C C CD u k C k C k C k Ct x z x − −
∂ ∂ ∂ ∂= + − + − + − ∂ ∂ ∂ ∂
(6)
By coupling the above equation with the surface reaction models depicted
in Chapter 8, the hybridization fraction of PCR products from microfluidic
microarray method can be solved.
During the modeling and simulation of hybridization kinetics, literature
values of parameters have been used. However, many of them are measured
based on the solution reactions which are not necessary same as those of
surface-based reactions [16, 360]. Moreover, the kinetics constant of DNA
hybridization may vary with different sequences. It is thus necessary to pursue
experimental measurements to find out the values of these parameters under
microfluidic conditions. In addition, the effect of microflow on DNA conformation
230
and later hybridization has to be studied and to be incorporated in the future
model [87, 110].
231
10: APPENDIX
10.1 COMSOL simulation steps for the kinetics study of microfluidic microarray hybridization
In this section, we provide a step-by-step guide based on the simulation
work of Gervais et al. [312]. The simulations use the multiphysics capabilities
built in the COMSOL program to simulate time-dependent concentration profiles
in the presence of convection, diffusion and DNA surface reaction under arbitrary
conditions. Geometry coupling is used to link the reaction occurring at the
surface to the reaction in the bulk. The specific example was used to generate
the data used in the analysis performed in Chapter 8. This tutorial will work on
COMSOL versions 3.5a. It may not work on earlier versions and cannot be
guaranteed to work on more advanced versions of the program (COMSOL
version 4.0 and up).
The physical model solves the dimensionless equations system
summarized in Chapter 8. The convection-diffusion PDE in the bulk is couple to
the DNA surface reaction ODE though a flux boundary condition at the bottom
wall. The resulting system is nonlinear due to the multiplied surface and bulk
concentration in the surface reaction equation.
232
10.1.1 Channel geometry construction
To simulate transport and reaction at a channel surface one must define
two different geometries in COMSOL: bulk geometry and a surface one. Since in
all microfluidic channels studied in this thesis, the channel width is larger than its
height, we proceed to a simplified 2-D model assuming parallel plate geometry.
The detail steps are list as follows:
1. Open “Multiphysics\Model Navigator”;
2. Click on “Add geometry”. Add a 2-D geometry named “Bulk” with
independent variables Lx and Hy (in that order to yield a normalized
length variable x* and normalized height variable z*, respectively,
as depicted in Chapter 8);
3. Click on “Add geometry”. Add a 1D geometry named “Surface” with
independent variable Lx;
4. Click “OK” to close window;
5. Select the “Bulk” in the geometry tabs; Go to “Draw\Draw
Objects\Rectangle-Square”. Draw a rectangle of dimension 2 × 1
with lower left base point located at the origin (0, 0). The channel
we seek to model has normalized length / ( )dLx x U t= ⋅ from 0 to 2
and normalized height /Hy z H= from 0 to 1, where x and z are the
real device dimension coordinates; td is the characteristic time scale
( 2dt H D= ). We fix the aspect ratio of our simulations and adjust
233
the length scale with a scaling factor ( sf ) to avoid consuming too
much computing powers.
6. Go to “Draw\Specify Objects\Point”, draw six points with Lx
coordinate “0.6, 0.8, 1.0, 1.2, 1.4, 1.6”, respectively.
7. Similarly, select the 1-D “Surface” geometry tab and draw a 2 unit-
long line in 18 segments with Lx coordinate “0, 0.6, 0.8, 1.0, 1.2,
1.4, 1.6, 2.0”, respectively.
Figure 10-1 The 2-D geometry used in the COMSOL simulation.
10.1.2 Choosing the physics models:
After the geometries have been constructed, we choose the proper
physics models to include the physical principles.
8. In “Multiphysics\Model Navigator”, select for the 2-D geometry
“Chemical Engineering Module\ Mass Transport\ Convection and
Diffusion\Transient Analysis”. Rename the dependent variable
234
“Conc” for the normalized bulk concentration variable ( *C ) and click
“Add”;
9. In the 1-D geometry, create a transient diffusion module
(convection is not necessary at the surface) with dependent
variable “Theta” for the normalized surface concentration of
hybridized target DNA ( *Θ );
10. In the 1-D geometry, create another transient diffusion module with
dependent variable “Eta” for the normalized surface concentration
of non-specifically adsorbed target DNA ( *η );
11. Click “OK” and return to COMSOL's main window;
10.1.3 Domain Coupling:
The variable “Theta” and “Eta” in the 1-D geometry must be redefined in
the 2-D domain with a different name. Similarly the variable “Conc” must be
redefined in the 1-D domain to represent the concentration at the wall ( *wC ).
Because we assume that the PDMS walls (the upper and side walls) do not
adsorb or retain any DNA molecules, the coupling is only applied to the bottom
wall (the glass substrate). The procedure is the following:
12. While in the “Bulk” Geometry, select “Options\ Extrusion Coupling
Variables\ Boundary Variables” to bring up the extrusion variables
window;
235
13. On the boundaries corresponding to the bottom wall enter the
following:
On the lower wall, create the variable “ConcWall = Conc”,
Under the Destination tab, select the “surface” geometry as the
destination and the lower wall boundary as the origin,
Under the Source Vertices tab, select all the vertices in the
boundary,
Under the Destination Vertices tab, select all the vertices in the
domain to which it corresponds in the 1-D geometry.
14. Repeat step 12 in the “Surface” geometry and create the other
extrusion variables “ThetaSurf = Theta” and “EtaSurf = Eta” which
links all the surface concentrations in 1-D domain to the lower
boundary in the 2-D domain;
10.1.4 Constant and Variable Specifications
As depicted in Chapter 8, a series of parameters have been used to scale
the dimensionless variables and they are either from experimental
measurements or from reference values. During COMSOL simulation, these
parameters are entered as global constants. Moreover, the non-dimensionalized
parameters, such as Pe and Da numbers, are calculated from the constants and
are inputted as global expressions.
236
15. In “Options\constants” enter the problems experimental
parameters, one per line, within a consistent unit system. The
constants entered are global:
Name Expression Description
c0 1e-8[mol/L] Initial bulk concentration of analyte (10 nM)
cs0 8.3e-9[mol/L*mm] Total number of surface probes (on one probe spot)
D 5e-5[mm^2/s] Diffusion coefficient of 21-mer oligonucleotides
Ds 5e-13[m^2/s] Surface diffusion coefficient of 21-mer oligonucleotides
he 0.03[mm] Channel height
L 2[mm] Channel length
U 5[mm/s] Average fluidic velocity (from experiment)
Lgeom 2 Length of the geometry
k3f 7.5e4[L/(mol*s)] Hybridization rate constant of bulk to surface
k3r 2e-4[1/s] Dissociation rate constant
ka 3e3[L/(mol*s)] Adsorption rate constant
kd 0.3[1/s] Desorption rate constant
Rt 4[nm] Gyration radius of target oligonucleotides
Na 6.022e23[1/mol] Avogadro constant
237
16. Select “Options\Global Expressions “. Enter the variables that apply
to both bulk and the surface:
Name Expression Description
Pe U*he/D Péclet number
Da1 ka*camax*he/D Damköhler number of the target adsorption process.
Da2 k2*camax*he/(Ds/he) Damköhler number of the surface-to-surface hybridization process.
Da3 k3*cs0*he/D Damköhler number of the bulk-to-surface hybridization process.
td he^2/D Diffusion time scale
sf Lgeom*td*U/L Scaling factor
k2 (k3*phi/Rp)*(16/3*pi) Kinetic association constant for nonspecific adsorption of target strands.
k2r k3r Kinetic dissociation constant for nonspecific adsorption of target strands.
epsilon1 c0*he/camax Ratio of bulk-phase targets to maximum adsorbable targets.
epsilon2 cs0/camax Ratio of surface adsorption capacity relative to hybridization capacity.
epsilon3 c0*he/cs0 Ratio of bulk-phase target numbers to maximum hybridizable target numbers.
KD kd/ka/c0 Dimensionless dissociation equilibrium constant for nonspecific adsorption of targets.
K2 k2r/k2/camax Dimensionless dissociation equilibrium constant for surface-to-surface hybridization of targets.
K3 k3r/k3/c0 Dimensionless dissociation equilibrium constant for bulk-to-surface hybridization of targets.
phi Ds/D Ratio between the surface diffusion coefficient (Ds) and the bulk diffusion coefficient (D).
Rp sqrt(1/(Na*cs0))/2 Radius of each probe molecule occupied on the glass surface.
camax (1-pi*Rp^2*Na*cs0) /(pi*Na*Rt^2)
ηmax at probe regions on the bottom wall.
camaxx 1/(pi*Na*Rt^2) ηmax at no-probe regions on the bottom wall.
Da1x ka*camaxx*he/D Damköhler number of the target adsorption process at no-probe regions.
238
17. In the “Bulk” geometry tab, select “Options\Expressions\Scalar
Expressions”. Enter the variables that apply to the bulk
Name Expression Description
V 6*Hy*(1-Hy) Normalized flow velocity profile
Rabs epsilon1*Da1*(Conc*(1-EtaSurf)-KD*EtaSurf) Dimensionless adsorption rate at probe regions
Rbhy epsilon3*Da3*(Conc*(1-ThetaSurf)-K3*ThetaSurf) Dimensionless hybridization rate at probe regions
Rabsx epsilon1*Da1x*(Conc*(1-EtaSurf)-KD*EtaSurf) Dimensionless adsorption rate at no-probe regions
18. In the “Surface” geometry tab, select
“Options\Expressions\Subdomain Expressions”, At the domains
where probe spots locate, enter the surface reaction rate as seen
from the surface:
Name Expression Description
Rabs epsilon1*Da1*(ConcWall*(1-Eta)-KD*Eta) Dimensionless adsorption rate at probe regions
Rshy phi*epsilon2*Da2*(Eta*(1-Theta)-K2*Theta) Dimensionless hybridization rate at probe regions
Rbhy epsilon3*Da3*(ConcWall*(1-Theta)-K3*Theta) Dimensionless adsorption rate at no-probe regions
239
10.1.5 Subdomain equation settings:
The subdomain settings describe the physics on a model’s main domain,
which is divided into subdomains. We can set different values for coefficients that
define the PDE on the subdomain. Moreover, material properties are also defined
in the subdomains.
19. In “Multiphysics\Model Navigator”, select the concentration model
with variable “Conc”. In “Physics\Subdomain settings” enter the
following parameter (linked to the variables previously defined) in
the convection-diffusion equation (“Conc” tab):
Time-scaling coefficient: δts = td
Diffusion coefficient: D anisotropic = (sf/Pe)^2 0 0 1 (Since the
normalization constants are different axially and vertically, the
effective diffusion in the geometry becomes anisotropic),
Reaction rate : R = 0 (there is no reaction in the subdomain)
Lx-velocity: u = sf *V (accounts for the normalized length)
“init” tab, initial condition can be 0 (start from empty) or any other
value.
leave the “element” tab unchanged,
20. In “Multiphysics\Model Navigator”, select the concentration model
with variable “Theta”. In “Physics\Subdomain settings” enter the
following:
Time-scaling coefficient: ts= td (since = t/td)
Diffusion coefficient: D isotropic = 0,
240
Reaction rate : for probe regions, R = Rbhy+Rshy/epsilon2; for no-
probe regions, R = 0
Leave the other tabs unchanged.
The model computes the time dependent hybridization rate at the surface.
This rate will vary with Hy depending on the concentration right above it in the
bulk (Cw).
21. In “Multiphysics\Model Navigator”, select the concentration model
with variable “Eta”. In “Physics\Subdomain settings” enter the
following:
Time-scaling coefficient: ts= td (since = t/td)
Diffusion coefficient: D isotropic = phi*(sf/Pe)^2,
Reaction rate : for probe regions, R = Rabs-Rshy; for no-probe
regions, R = Rabs
Leave the other tabs unchanged.
The model computes the time dependent adsorption rate at the surface.
This rate will vary with z depending on the concentration right above it in the bulk
(Cw), surface diffusion coefficient (Ds), and probe coverage ( 0Θ ).
241
10.1.6 Boundary conditions settings:
Boundary conditions define the interface between the model geometry and
its surroundings. Different boundary conditions can be specified on different
boundaries.
22. For each of the models (variables: Conc, Theta, and Eta) enter the
boundary conditions in “Physics\boundary settings”:
a. for the “Conc” variable:
i. boundary (inlet): concentration c0= 1 or
insulation/symmetry for static hybridization,
ii. boundary (upper wall): flux = 0,
iii. boundary (lower wall with probe spots):
flux= -Rabs/epsilon1-Rbhy/epsilon3,
iv. boundary (lower wall without probe spots):
flux= - Rabsx/epsilon1,
v. boundary (outlet): convective flux.
b. for the “ Theta “ variable:
i. boundary (left vertex): flux=0,
ii. boundary (right vertex): flux=0.
c. for the “ Eta “ variable:
i. boundary (left vertex): flux=0,
242
ii. boundary (right vertex): flux=0.
10.1.7 Meshing
A mesh is a partition of the geometry model into small units of simple
shapes. It must be fine enough to resolve the sharp spatial distribution of
analytes that may occur near the reacting walls. In the bulk, some memory can
be saved by specifying a coarser mesh since the gradients present there are
lower than at the surface. We therefore propose the following meshing method:
23. Select “Mesh\Mesh parameters” from the main menu to bring up
the customized mesh window. For the “Bulk” geometry, enter the
following:
In the subdomain tab, enter a maximum element size of 0.05. This
size limits ensures that, for a geometry of height 1 as in the present
case, there will always be at least 20 grid points across it.
In the boundary tab, enter a maximum element size of 0.005 along
the reactive walls to ensure a finer characterization of these
regions.
Click on remesh to recreate the mesh. The default mesh growth
rates are sufficient in our case.
24. Select the “Surface” geometry and select Mesh\Mesh parameters”
from the main menu;
In the subdomain tab, enter a maximum element size of 0.004 for
all domains. This number of points at the surface will be sufficient to
243
match those specified at the boundary in the “Bulk” geometry. Here
a different number from 0.005 was used to avoid computational
noise in the simulation results.
10.1.8 Solver Parameters and Solver Manager
COMSOL Multiphysics includes a number of different solvers for PDE-
based problems. However, we do not need to select a solver explicitly in most
cases. Once the “Analysis Types” are selected as “Transient” based on our
convection-diffusion model, COMSOL will automatically choose a solver
compatible to our model. We then have to set the time duration and stepping for
the simulation studies.
25. In “solver\solver parameters”, select the “general” tab and specify
the following: Time stepping: times = range(0,1,180), for a 3-min
hybridization. Other tabs can be left as they are. Click “Ok” to return
to the main window.
26. In the “solver\solver manager” window, select the “initial value” tab
and specify: Initial value: “Initial value expression”, the rest can be
left untouched. In the “solve for” and “output” tabs, values can be
left as default (i.e. solves for all variables). In some particular
cases, it may save time to solve only for certain variables.
However, all coupled variables must always be solved together or
the solution will yield a trivial solution, Click “OK” to return to the
main menu.
244
10.1.9 Post-processing and visualization
COMSOL Multiphysics provides numerous post-processing and
visualization tools for the analysis of simulation results from the solvers. For
example, “Domain Plot” has been used to render the colormap of the bulk
concentration inside microchannels; “Cross-section Plot” was used to draw the
change of a variable along a specified line; the hybridization kinetics curve at a
spot was plotted with “Subdomain Integration” under a specified time range.
245
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